Water Encyclopedia: Water Quality and Resource Development [2, 1 ed.] 9780471736868, 0471736864

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WATER ENCYCLOPEDIA

WATER QUALITY AND RESOURCE DEVELOPMENT

WATER ENCYCLOPEDIA Editor-in-Chief Jay Lehr, Ph.D. Senior Editor Jack Keeley Associate Editor Janet Lehr Information Technology Director Thomas B. Kingery III

Editorial Staff Vice President, STM Books: Janet Bailey Editorial Director, STM Encyclopedias: Sean Pidgeon Executive Editor: Bob Esposito Director, Book Production and Manufacturing: Camille P. Carter Production Manager: Shirley Thomas Senior Production Editor: Kellsee Chu Illustration Manager: Dean Gonzalez Editorial Program Coordinator: Jonathan Rose

WATER ENCYCLOPEDIA

WATER QUALITY AND RESOURCE DEVELOPMENT Jay Lehr, Ph.D. Editor-in-Chief Jack Keeley Senior Editor Janet Lehr Associate Editor Thomas B. Kingery III Information Technology Director

The Water Encyclopedia is available online at http://www.mrw.interscience.wiley.com/eow/

A John Wiley & Sons, Inc., Publication

Copyright  2005 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services please contact our Customer Care Department within the U.S. at 877-762-2974, outside the U.S. at 317-572-3993 or fax 317-572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print, however, may not be available in electronic format. Library of Congress Cataloging-in-Publication Data is available. Lehr, Jay Water Encyclopedia: Water Quality and Resource Development ISBN 0-471-73686-4 ISBN 0-471-44164-3 (Set) Printed in the United States of America 10 9 8 7 6 5 4 3 2 1

CONTENTS Preface Contributors

ix xi

Trace Element Contamination in Groundwater of District Hardwar, Uttaranchal, India Iron Bacteria Cartridge Filters for Iron Removal Irrigation Water Quality in Areas Adjoining River Yamuna At Delhi, India Water Sampling and Laboratory Safety Municipal Solid Waste Landfills—Water Quality Issues Land Use Effects on Water Quality Monitoring Lipophilic Contaminants in the Aquatic Environment using the SPMD-TOX Paradigm Use of Luminescent Bacteria and the Lux Genes For Determination of Water Quality Water Quality Management Water Quality Management and Nonpoint Source Control Water Quality Management in an Urban Landscape Water Quality Management in the U.S.: History of Water Regulation Water Quality Management in a Forested Landscape Trace Metal Speciation Metal Ion Humic Colloid Interaction Heavy Metal Uptake Rates Among Sediment Dwelling Organisms Methemoglobinemia Microbial Activities Management Microbial Dynamics of Biofilms Microbial Enzyme Assays for Detecting Heavy Metal Toxicity Microbial Forms in Biofouling Events Microbiological Quality Control in Distribution Systems Water Quality Models for Developing Soil Management Practices Water Quality Modeling—Case Studies Field Sampling and Monitoring of Contaminants Water Quality Models: Chemical Principles Water Quality Models: Mathematical Framework Environmental Applications with Submitochondrial Particles Interest in the Use of an Electronic Nose for Field Monitoring of Odors in the Environment Oil-Field Brine Oil Pollution Indicator Organisms pH Perchloroethylene (PCE) Removal A Primer on Water Quality Overview of Analytical Methods of Water Analyses With Specific Reference to EPA Methods for Priority Pollutant Analysis Source-Water Protection Protozoa in Water

Water Quality Control Acid Mine Drainage—Extent and Character The Control of Algal Populations in Eutrophic Water Bodies Arsenic Compounds in Water Arsenic Health Effects Background Concentration of Pollutants Waterborne Bacteria Water Assessment and Criteria Physiological Biomarkers and the Trondheim Biomonitoring System Biomarkers, Bioindicators, and the Trondheim Biomonitoring System Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs Biochemical Oxygen Demand and Other Organic Pollution Measures Biodegradation Bioluminescent Biosensors for Toxicity Testing Biomanipulation Genomic Technologies in Biomonitoring Macrophytes as Biomonitors of Trace Metals Biosorption of Toxic Metals Bromide Influence on Trihalomethane and Haloacetic Acid Formation Activated Carbon: Ion Exchange and Adsorption Properties Activated Carbon—Powdered Chlorination Chlorination By-Products Classification and Environmental Quality Assessment in Aquatic Environments Coagulation and Flocculation in Practice Colloids and Dissolved Organics: Role in Membrane and Depth Filtration Column Experiments in Saturated Porous Media Studying Contaminant Transport Cytochrome P450 Monooxygenase as an Indicator of PCB/Dioxin-Like Compounds in Fish Water Related Diseases Dishwashing Water Quality Properties Disinfection By-Product Precursor Removal from Natural Waters Alternative Disinfection Practices and Future Directions for Disinfection By-Product Minimization Water Quality Aspects of Dredged Sediment Management The Economics of Water Quality Understanding Escherichia Coli O157:H7 and the Need for Rapid Detection in Water Eutrophication and Organic Loading

1 2 7 15 18 20 24 28 29 33 37 41 45 50 58 64 68 74 79 86 88 91 94 98 99 103

106 111 112 115

118 122 127 136 142 v

143 149 152 155 161 163 169

170 172 176 184 189 193 199 202 205 211 219 223 228 233 239 243 248 255 263 269 273 278 281 284 290 292 294 299 301

304 311 313

vi

CONTENTS

Water Quality Water Quality Emerging and Recalcitrant Compounds in Groundwater Road Salt Review of River Water Quality Modeling Software Tools River Water Quality Calibration Salmonella: Monitoring and Detection in Drinking Water Lysimeter Soil Water Sampling Regulatory and Security Requirements for Potable Water A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts Remediation and Bioremediation of Selenium-Contaminated Waters Shellfish Growing Water Classification Sorptive Filtration Quality of Water in Storage Quality of Water Supplies The Submitochondrial Particle Assay as a Biological Monitoring Tool Microscale Test Relationships to Responses to Toxicants in Natural Systems Toxicity Identification Evaluation Whole Effluent Toxicity Controls Development and Application of Sediment Toxicity Tests for Regulatory Purposes Algal Toxins in Water Ground Water Quality in Areas Adjoining River Yamuna at Delhi, India Chlorine Residual Source Water Quality Management Dose-Response of Mussels to Chlorine Metallothioneins as Indicators of Trace Metal Pollution Amphipod Sediment Toxicity Tests Ciliated Protists as Test Organisms in Toxicity Assessment SOFIE: An Optimized Approach for Exposure Tests and Sediment Assays Passive Treatment of Acid Mine Drainage (Wetlands) Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality Lead and its Health Effects Microbial Detection of Various Pollutants as an Early Warning System for Monitoring of Water Quality and Ecological Integrity of Natural Resources, in Russia Luminescent Bacterial Biosensors for the Rapid Detection of Toxicants Development and Application of Sediment Toxicity Test for Regulatory Purposes Eh

314 316 316 319 325 331 337 340 343

350 355 360 362 367 370 376 379 380 382 383 387 392 398 399 401 406 408 413 418 423 426 432

440 453 458 464

Water Resource Development and Management Water Resources Challenges in the Arab World Effluent Water Regulations in Arid Lands

470 475

California—Continually the Nation’s Leader in Water Use Lessons from the Rising Caspian Institutional Aspects of Water Management in China Will Water Scarcity Limit China’s Agricultural Potential? Water and Coastal Resources Water Use Conservation and Efficiency Conservation of Water The Development of American Water Resources: Planners, Politicians, and Constitutional Interpretation Water Markets: Transaction Costs and Institutional Options Averting Water Disputes Water Supply and Water Resources: Distribution System Research Drought in the Dust Bowl Years Drought Management Planning Drought and Water Supply Management Assessment of Ecological Effects in Water-Limited Environments Reaching Out: Public Education and Community Involvement in Groundwater Protection Integration of Environmental Impacts into Water Resources Planning The Expansion of Federal Water Projects Flood Control History in the Netherlands Food and Water in an Emergency Water Demand Forecasting Remote Sensing and GIS Application in Water Resources Globalization of Water Water Science Glossary of Terms Harvesting Rainwater Urban Water Resource and Management in Asia: Ho Chi Minh City Hydropower—Energy from Moving Water Water Markets in India: Economic and Institutional Aspects Water Resources of India Water Infrastructure and Systems Overview and Trends in the International Water Market Best Management Practices for Water Resources Integrated Water Resources Management (IWRM) Management of Water Resources for Drought Conditions Water Resources Management NASA Helping to Understand Water Flow in the West Transboundary Water Conflicts in the Nile Basin Planning and Managing Water Infrastructure Application of the Precautionary Principle to Water Science Water Pricing Spot Prices, Option Prices, and Water Markets Water Managed in the Public Trust

478 480 484 488 489 489 495

498 499 501 509 511 514 515 516 518 520 522 524 526 529 531 536 541 548 552 554 555 559 567 568 570 574 576 586 587 590 594 595 603 606 608

CONTENTS

Water Recycling and Reuse: The Environmental Benefits State and Regional Water Supply River Basin Decisions Support Systems Water Resource Sustainability: Concepts and Practices The Provision of Drinking Water and Sanitation in Developing Countries Sustainable Management of Natural Resources Sustainable Water Management On Mediterranean Islands: Research and Education Meeting Water Needs in Developing Countries with Tradable Rights Water Use in the United States

610 613 619 624 630 633

638 643 645

vii

How We Use Water in These United States Valuing Water Resources Water—Here, There, and Everywhere in Canada Water Conservation—Every Drop Counts in Canada Ecoregions: A Spatial Framework for Environmental Management Flood of Portals on Water Fuzzy Criteria for Water Resources Systems Performance Evaluation Participatory Multicriteria Flood Management Water Resources Systems Analysis

650 653

674 678 683

Index

689

656 660 667 668

PREFACE Cities, towns, states, and nations must manage their water resources wisely from both a quality and a quantitative perspective. If we do otherwise and manage them with a narrow perspective, the public’s needs will not be adequately met. In this volume of the Water Encyclopedia, authors from around the world have described a myriad of problems relating to individual water bodies as well as to geographic water resources and their management dilemmas. Humans and other living creatures contribute to our water quality problems. Neither can be fully controlled. Even the nature of contaminant sources and programs for their elimination can be difficult to design. This volume contains the best and brightest ideas and case studies relating to the areas of water quality and resource management problems. Quality problems deal with a diverse suite of subjects ranging widely from acid mine drainage to biosorption, colloids, eutrophication, protozoa, and recalcitrant compounds. Resource management features drought studies, flood control, river basin management, perennial overdraft, water banking, and a host of other subjects. The perspective of scientists from nearly every continent of the world offers a truly catholic view of

attitudes and biases harbored in different regions and how they affect scientific and regulatory outcomes. The editors cannot imagine what has been left out, but we know of course that readers will at times come up short of finding an exact match to a problem they face. We hope they will contact us at our website and allow us the opportunity of adding additional subjects to our encyclopedia. At the same time, the reader will understand that many subjects in the area of water quality may have been addressed in our Surface Water category. It was often difficult to determine where an investigator would be more likely to look for a piece of information. (The complete index of all five volumes appears in the Ground Water volume as well as on our website.) We trust all users of this encyclopedia will find it detailed, informative, and interesting. Not only are a wide range of subjects treated, but authors choose varying approaches to presenting their data to readers who may be professionals, students, researchers, as well as individuals simply satisfying their intellectual curiosity. We hope we are successfully serving all of these populations in some useful way. Jay Lehr Jack Keeley

ix

CONTRIBUTORS Joanna Davies, Syngenta, Bracknell, Berkshire, United Kingdom, The Control of Algal Populations in Eutrophic Water Bodies Maria B. Davoren, Dublin Institute of Technology, Dublin, Ireland, Luminescent Bacterial Biosensors for the Rapid Detection of Toxicants T.A. Delvalls, Facultad de Ciencias del Mar y Ambientales, Cadiz, ´ Spain, Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts Nicolina Dias, Centro de Engenharia Biol´ogica, Braga, Portugal, Ciliated Protists as Test Organisms in Toxicity Assessment Galina Dimitrieva-Moats, University of Idaho, Moscow, Idaho, Microbial Detection of Various Pollutants as an Early Warning System for Monitoring of Water Quality and Ecological Integrity of Natural Resources, in Russia Halanaik Diwakara, University of South Australia, Adelaide, Australia, Water Markets in India: Economic and Institutional Aspects Francis G. Doherty, AquaTox Research, Inc., Syracuse, New York, The Submitochondrial Particle Assay as a Biological Monitoring Tool Antonia A. Donta, University of Munster, ¨ Centre for Environmental Research, Munster, ¨ Germany, Sustainable Water Management On Mediterranean Islands: Research and Education Timothy J. Downs, Clark University, Worcester, Massachusetts, Field Sampling and Monitoring of Contaminants, State and Regional Water Supply, Water Resource Sustainability: Concepts and Practices Hiep N. Duc, Environment Protection Authority, NSW, Bankstown, New South Wales Australia, Urban Water Resource and Management in Asia: Ho Chi Minh City Suzanne Du Vall Knorr, Ventura County Environmental Health Division, Ventura, California, Regulatory and Security Requirements for Potable Water Sandra Dunbar, Napier University, Edinburgh, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Diane Dupont, Brock University, St. Catharines, Ontario, Canada, Valuing Water Resources Michael P. Dziewatkoski, Mettler-Toledo Process Analytical, Woburn, Massachusetts, pH Energy Information Administration—Department of Energy, Hydropower—Energy from Moving Water Environment Canada, Water—Here, There, and Everywhere in Canada, Water Conservation—Every Drop Counts in Canada Environmental Protection Agency, Water Recycling and Reuse: The Environmental Benefits M. Eric Benbow, Michigan State University, East Lansing, Michigan, Road Salt Teresa W.-M. Fan, University of Louisville, Louisville, Kentucky, Remediation and Bioremediation of Selenium-Contaminated Waters Federal Emergency Management Agency, Food and Water in an Emergency Huan Feng, Montclair State University, Montclair, New Jersey, Classification and Environmental Quality Assessment in Aquatic Environments ´ N. Buceta Fernandez, Centro de Estudios de Puertos y Costas, Madrid, Spain, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts Peter D. Franzmann, CSIRO Land and Water, Floreat, Australia, Microbial Activities Management Christian D. Frazar, Silver Spring, Maryland, Biodegradation Rajiv Gandhi Chair, Jawaharlal Nehru University, New Delhi, India, Oil Pollution Suduan Gao, USDA–ARS, Parlier, California, Eh Horst Geckeis, Institut fur ¨ Nukleare Entsorgung, Karlsruhe, Germany, Metal Ion Humic Colloid Interaction Robert Gensemer, Parametrix, Corvallis, Oregon, Effluent Water Regulations in Arid Lands ´ Mario Abel Goncalves, ¸ Faculdade de Ciˆencias da Universidade de Lisoba, Lisoba, Portugal, Background Concentration of Pollutants Neil S. Grigg, Colorado State University, Fort Collins, Colorado, Planning and Managing Water Infrastructure, Drought and Water Supply

Absar Alum, Arizona State University, Tempe, Arizona, Water Quality Management in the U.S.: History of Water Regulation Mohammad N. Almasri, An-Najah National University, Nablus, Palestine, Best Management Practices for Water Resources Linda S. Andrews, Mississippi State University, Biloxi, Mississippi, Shellfish Growing Water Classification, Chlorine Residual Hannah Aoyagi, University of California, Irvine, California, Cytochrome P450 Monooxygenase as an Indicator of PCB/Dioxin-Like Compounds in Fish ¨ Industrie Service GmbH, Munchen, Robert Artinger, TUV ¨ Germany, Column Experiments in Saturated Porous Media Studying Contaminant Transport Mukand Singh Babel, Asian Institute of Technology, Pathumthani, Thailand, Conservation of Water, Integrated Water Resources Management (IWRM) Mark Bailey, Centre for Ecology and Hydrology–Oxford, Oxford, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Shimshon Balanson, Cleveland State University, Cleveland, Ohio, Macrophytes as Biomonitors of Trace Metals Christine L. Bean, University of New Hampshire, Durham, New Hampshire, Protozoa in Water Jennifer Bell, Napier University, Edinburgh, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Lieven Bervoets, University of Antwerp, Antwerp, Belgium, Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs J.M. Blasco, Instituto de Ciencias Marinas de Andalucı´a, Cadiz, ´ Spain, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts Ronny Blust, University of Antwerp, Antwerp, Belgium, Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs Marta Bryce, CEPIS/PAHO, Delft, The Netherlands, Flood of Portals on Water Mario O. Buenfil-Rodriguez, National University of Mexico, Cuernavaca, Morelos, Mexico, Water Use Conservation and Efficiency Jacques Buffle, University of Geneva, Geneva, Switzerland, Colloids and Dissolved Organics: Role in Membrane and Depth Filtration Zia Bukhari, American Water, Belleville, Illinois, Understanding Escherichia Coli O157:H7 and the Need for Rapid Detection in Water John Cairns, Jr., Virginia Polytechnic Institute and State University, Blacksburg, Virginia, Microscale Test Relationships to Responses to Toxicants in Natural Systems Michael J. Carvan III, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, Genomic Technologies in Biomonitoring M.C. Casado-Mart´ınez, Facultad de Ciencias del Mar y Ambientales, Cadiz, ´ Spain, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts ´ ´ Angel Tomas Del Valls Casillas, Universidad de Cadiz, Cadiz, Spain, Amphipod Sediment Toxicity Tests, Development and Application of Sediment Toxicity Test for Regulatory Purposes Teresa A. Cassel, University of California, Davis, California, Remediation and Bioremediation of Selenium-Contaminated Waters Augusto Cesar, Universidad de Cadiz, Cadiz, Spain, Amphipod Sediment Toxicity Tests K.W. Chau, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Water Quality Models: Mathematical Framework Paulo Chaves, Water Resources Research Center, Kyoto University, Japan, Quality of Water in Storage Shankar Chellam, University of Houston, Houston, Texas, Bromide Influence on Trihalomethane and Haloacetic Acid Formation X. Chris Le, University of Alberta, Edmonton, Alberta, Canada, Arsenic Compounds in Water Russell N. Clayshulte, Aurora, Colorado, Water Quality Management in an Urban Landscape Gail E. Cordy, U.S. Geological Survey, A Primer on Water Quality Rupali Datta, University of Texas, San Antonio, Texas, Lead and its Health Effects

xi

xii

CONTRIBUTORS

Management, Drought Management Planning, Water Infrastructure and Systems, Water Resources Management ˚ ˚ Hakan Hakanson, University of Lund, Lund, Sweden, Dishwashing Water Quality Properties Carol J. Haley, Virginia Water Resources Research Center, Management of Water Resources for Drought Conditions M.G.J Hartl, Environmental Research Institute, University College Cork, Ireland, Development and Application of Sediment Toxicity Tests for Regulatory Purposes Roy C. Haught, U.S. Environmental Protection Agency, Water Supply and Water Resources: Distribution System Research Joanne M. Hay, Lincoln Ventures, Ltd., Lincoln, New Zealand, Biochemical Oxygen Demand and Other Organic Pollution Measures Richard M. Higashi, University of California, Davis, California, Remediation and Bioremediation of Selenium-Contaminated Waters A.Y. Hoekstra, UNESCO–IHE Institute for Water Education, Delft, The Netherlands, Globalization of Water Charles D.D. Howard, Water Resources, Victoria, British Columbia, Canada, River Basin Decisions Support Systems Margaret S. Hrezo, Radford University, Virginia, Management of Water Resources for Drought Conditions Enos C. Inniss, University of Texas, San Antonio, Texas, Perchloroethylene (PCE) Removal James A. Jacobs, Environmental Bio-Systems, Inc., Mill Valley, California, Emerging and Recalcitrant Compounds in Groundwater Chakresh K. Jain, National Institute of Hydrology, Roorkee, India, Water Quality Management, Trace Element Contamination in Groundwater of District Hardwar, Uttaranchal, India, Ground Water Quality in Areas Adjoining River Yamuna at Delhi, India, Irrigation Water Quality in Areas Adjoining River Yamuna At Delhi, India Sanjay Kumar Jain, National Institute of Hydrology, Roorkee, India, Remote Sensing and GIS Application in Water Resources Sharad K. Jain, National Institute of Hydrology, Roorkee, Uttranchal, India, Water Resources of India H.A. Jenner, KEMA Power Generation and Sustainables, Arnhem, The Netherlands, Dose-Response of Mussels to Chlorine Y. Jiang, Hong Kong Baptist University, Kowloon, Hong Kong, Algal Toxins in Water B. Ji, Hong Kong Baptist University, Kowloon, Hong Kong, Algal Toxins in Water ´ N. Jimenez-Tenorio, Facultad de Ciencias del Mar y Ambientales, Cadiz, ´ Spain, Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality Zhen-Gang Ji, Minerals Management Service, Herndon, Virginia, Water Quality Modeling—Case Studies, Water Quality Models: Chemical Principles Erik Johansson, GS Development AB, Malm¨o, Sweden, Dishwashing Water Quality Properties B. Thomas Johnson, USGS—Columbia Environmental Research Center, Columbia, Missouri, Monitoring Lipophilic Contaminants in the Aquatic Environment using the SPMD-TOX Paradigm Anne Jones-Lee, G. Fred Lee & Associates, El Macero, California, Water Quality Aspects of Dredged Sediment Management, Municipal Solid Waste Landfills—Water Quality Issues Dick de Jong, IRC International Water and Sanitation Centre, Delft, The Netherlands, Flood of Portals on Water Jagath J. Kaluarachchi, Utah State University, Logan, Utah, Best Management Practices for Water Resources Atya Kapley, National Environmental Engineering Research Institute, CSIR, Nehru Marg, Nagpur, India, Salmonella: Monitoring and Detection in Drinking Water I. Katsoyiannis, Aristotle University of Thessaloniki, Thessaloniki, Greece, Arsenic Health Effects Absar A. Kazmi, Nishihara Environment Technology, Tokyo, Japan, Activated Carbon—Powdered, Chlorination Keith O. Keplinger, Texas Institute for Applied Environmental Research, Stephenville, Texas, The Economics of Water Quality Kusum W. Ketkar, Jawaharlal Nehru University, New Delhi, India, Oil Pollution Ganesh B. Keremane, University of South Australia, Adelaide, Australia, Harvesting Rainwater

Rebecca D. Klaper, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, Genomic Technologies in Biomonitoring Toshiharu Kojiri, Water Resources Research Center, Kyoto University, Japan, Quality of Water in Storage Ken’ichirou Kosugi, Kyoto University, Kyoto, Japan, Lysimeter Soil Water Sampling Manfred A. Lange, University of Munster, ¨ Centre for Environmental Research, Munster, ¨ Germany, Sustainable Water Management On Mediterranean Islands: Research and Education ´ eric ´ Fred Lasserre, Universit´e Laval, Ste-Foy, Qu´ebec, Canada, Water Use in the United States N.K. Lazaridis, Aristotle University, Thessaloniki, Greece, Sorptive Filtration Jamie R. Lead, University of Birmingham, Birmingham, United Kingdom, Trace Metal Speciation G. Fred Lee, G. Fred Lee & Associates, El Macero, California, Water Quality Aspects of Dredged Sediment Management, Municipal Solid Waste Landfills—Water Quality Issues Terence R. Lee, Santiago, Chile, Water Markets: Transaction Costs and Institutional Options, The Provision of Drinking Water and Sanitation in Developing Countries, Spot Prices, Option Prices, and Water Markets, Meeting Water Needs in Developing Countries with Tradable Rights Markku J. Lehtola, National Public Health Institute, Kuopio, Finland, Microbiological Quality Control in Distribution Systems Gary G. Leppard, National Water Research Institute, Burlington, Ontario, Canada, Colloids and Dissolved Organics: Role in Membrane and Depth Filtration Mark LeChevallier, American Water, Voorhees, New Jersey, Understanding Escherichia Coli O157:H7 and the Need for Rapid Detection in Water Nelson Lima, Centro de Engenharia Biol´ogica, Braga, Portugal, Ciliated Protists as Test Organisms in Toxicity Assessment Maria Giulia Lionetto, Universita` di Lecce, Lecce, Italy, Metallothioneins as Indicators of Trace Metal Pollution Jody W. Lipford, PERC, Bozeman, Montana, and Presbyterian College, Clinton, South Carolina, Averting Water Disputes Baikun Li, Pennsylvania State University, Harrisburg, Pennsylvania, Iron Bacteria, Microbial Dynamics of Biofilms, Microbial Forms in Biofouling Events Rongchao Li, Delft University of Technology, Delft, The Netherlands, Transboundary Water Conflicts in the Nile Basin, Institutional Aspects of Water Management in China, Flood Control History in the Netherlands Bryan Lohmar, Economic Research Service, U.S. Department of Agriculture, Will Water Scarcity Limit China’s Agricultural Potential? ´ Inmaculada Riba Lopez, Universidad de Cadiz, Cadiz, Spain, Amphipod Sediment Toxicity Tests M.X. Loukidou, Aristotle University of Thessaloniki, Thessaloniki, Greece, Biosorption of Toxic Metals Scott A. Lowe, Manhattan College, Riverdale, New York, Eutrophication and Organic Loading G. Lyberatos, University of Ioannina, Agrinio, Greece, Cartridge Filters for Iron Removal Kenneth M. Mackenthun, Arlington, Virginia, Water Quality Tarun K. Mal, Cleveland State University, Cleveland, Ohio, Macrophytes as Biomonitors of Trace Metals Philip J. Markle, Whittier, California, Toxicity Identification Evaluation, Whole Effluent Toxicity Controls James T. Markweise, Neptune and Company, Inc., Los Alamos, New Mexico, Assessment of Ecological Effects in Water-Limited Environments, Effluent Water Regulations in Arid Lands Pertti J. Martikainen, University of Kuopio, Kuopio, Finland, Microbiological Quality Control in Distribution Systems M.L. Mart´ın-D´ıaz, Instituto de Ciencias Marinas de Andaluc´ıa, Cadiz, ´ Spain, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts, Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality Maria del Carmen Casado Mart´ınez, Universidad de Cadiz, Cadiz, Spain, Amphipod Sediment Toxicity Tests K.A. Matis, Aristotle University, Thessaloniki, Greece, Sorptive Filtration Lindsay Renick Mayer, Goddard Space Flight Center, Greenbelt, Maryland, NASA Helping to Understand Water Flow in the West

CONTRIBUTORS Mark C. Meckes, U.S. Environmental Protection Agency, Water Supply and Water Resources: Distribution System Research Richard W. Merritt, Michigan State University, East Lansing, Michigan, Road Salt Richard Meyerhoff, CDM, Denver, Colorado, Effluent Water Regulations in Arid Lands J. Michael Wright, Harvard School of Public Health, Boston, Massachusetts, Chlorination By-Products Cornelis J.H. Miermans, Institute for Inland Water Management and Waste Water Treatment–RIZA, Lelystad, The Netherlands, SOFIE: An Optimized Approach for Exposure Tests and Sediment Assays Ilkka T. Miettinen, National Public Health Institute, Kuopio, Finland, Microbiological Quality Control in Distribution Systems Dusan P. Miskovic, Northwood University, West Palm Beach, Florida, Oil-Field Brine Diana Mitsova-Boneva, University of Cincinnati, Cincinnati, Ohio, Quality of Water Supplies Tom Mohr, Santa Clara Valley Water District, San Jose, California, Emerging and Recalcitrant Compounds in Groundwater M.C. Morales-Caselles, Facultad de Ciencias del Mar y Ambientales, Cadiz, ´ Spain, Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality National Drought Mitigation Center, Drought in the Dust Bowl Years National Water-Quality Assessment (NAWQA) Program—U.S. Geological Survey, Source-Water Protection Jennifer Nelson, The Groundwater Foundation, Lincoln, Nebraska, Reaching Out: Public Education and Community Involvement in Groundwater Protection Anne Ng, Swinburne University of Technology, Hawthorne, Victoria, Australia, River Water Quality Calibration, Review of River Water Quality Modeling Software Tools Jacques Nicolas, University of Liege, Arlon, Belgium, Interest in the Use of an Electronic Nose for Field Monitoring of Odors in the Environment Ana Nicolau, Centro de Engenharia Biol´ogica, Braga, Portugal, Ciliated Protists as Test Organisms in Toxicity Assessment Diana J. Oakes, University of Sydney, Lidcombe, Australia, Environmental Applications with Submitochondrial Particles Oladele A. Ogunseitan, University of California, Irvine, California, Microbial Enzyme Assays for Detecting Heavy Metal Toxicity, Cytochrome P450 Monooxygenase as an Indicator of PCB/Dioxin-Like Compounds in Fish J. O’Halloran, Environmental Research Institute, University College Cork, Ireland, Development and Application of Sediment Toxicity Tests for Regulatory Purposes Victor Onwueme, Montclair State University, Montclair, New Jersey, Classification and Environmental Quality Assessment in Aquatic Environments Alper Ozkan, Selcuk University, Konya, Turkey, Coagulation and Flocculation in Practice Neil F. Pasco, Lincoln Ventures, Ltd., Lincoln, New Zealand, Biochemical Oxygen Demand and Other Organic Pollution Measures B.J.C. Perera, Swinburne University of Technology, Hawthorne, Victoria, Australia, River Water Quality Calibration, Review of River Water Quality Modeling Software Tools Jim Philip, Napier University, Edinburgh, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Laurel Phoenix, Green Bay, Wisconsin, Source Water Quality Management, Water Managed in the Public Trust Randy T. Piper, Dillon, Montana, Overview and Trends in the International Water Market John K. Pollak, University of Sydney, Lidcombe, Australia, Environmental Applications with Submitochondrial Particles ¨ Dorte Poszig, University of Munster, ¨ Centre for Environmental Research, Munster, ¨ Germany, Sustainable Water Management On Mediterranean Islands: Research and Education Hemant J. Purohit, National Environmental Engineering Research Institute, CSIR, Nehru Marg, Nagpur, India, Salmonella: Monitoring and Detection in Drinking Water Shahida Quazi, University of Texas, San Antonio, Texas, Lead and its Health Effects S. Rajagopal, Radboud University Nijmegen, Toernooiveld, Nijmegen, The Netherlands, Dose-Response of Mussels to Chlorine

xiii

Krishna Ramanujan, Goddard Space Flight Center, Greenbelt, Maryland, NASA Helping to Understand Water Flow in the West Lucas Reijnders, University of Amsterdam, Amsterdam, The Netherlands, Sustainable Management of Natural Resources Steven J. Renzetti, Brock University, St. Catharines, Ontario, Canada, Water Demand Forecasting, Water Pricing, Valuing Water Resources Martin Reuss, Office of History Headquarters U.S. Army Corps of Engineers, The Development of American Water Resources: Planners, Politicians, and Constitutional Interpretation, The Expansion of Federal Water Projects I. Riba, Facultad de Ciencias del Mar y Ambientales, Cadiz, ´ Spain, Biomarkers and Bioaccumulation: Two Lines of Evidence to Assess Sediment Quality, A Weight of Evidence Approach to Characterize Sediment Quality Using Laboratory and Field Assays: An Example For Spanish Coasts Matthew L. Rise, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, Genomic Technologies in Biomonitoring Arthur W. Rose, Pennsylvania State University, University Park, Pennsylvania, Acid Mine Drainage—Extent and Character, Passive Treatment of Acid Mine Drainage (Wetlands) Barry H. Rosen, US Fish & Wildlife Service, Vero Beach, Florida, Waterborne Bacteria Serge Rotteveel, Institute for Inland Water Management and Waste Water Treatment–RIZA, Lelystad, The Netherlands, SOFIE: An Optimized Approach for Exposure Tests and Sediment Assays Timothy J. Ryan, Ohio University, Athens, Ohio, Water Sampling and Laboratory Safety Randall T. Ryti, Neptune and Company, Inc., Los Alamos, New Mexico, Assessment of Ecological Effects in Water-Limited Environments Masaki Sagehashi, University of Tokyo, Tokyo, Japan, Biomanipulation Basu Saha, Loughborough University, Loughborough, United Kingdom, Activated Carbon: Ion Exchange and Adsorption Properties Md. Salequzzaman, Khulna University, Khulna, Bangladesh, Ecoregions: A Spatial Framework for Environmental Management Dibyendu Sarkar, University of Texas, San Antonio, Texas, Lead and its Health Effects Peter M. Scarlett, Winfrith Technology Centre, Dorchester, Dorset, United Kingdom, The Control of Algal Populations in Eutrophic Water Bodies Trifone Schettino, Universita` di Lecce, Lecce, Italy, Metallothioneins as Indicators of Trace Metal Pollution Lewis Schneider, North Jersey District Water Supply Commission, Wanaque, New Jersey, Classification and Environmental Quality Assessment in Aquatic Environments Wolfram Schuessler, Institut fur ¨ Nukleare Entsorgung, Karlsruhe, Germany, Column Experiments in Saturated Porous Media Studying Contaminant Transport K.D. Sharma, National Institute of Hydrology, Roorkee, India, Water Quality Management Mukesh K. Sharma, National Institute of Hydrology, Roorkee, India, Ground Water Quality in Areas Adjoining River Yamuna at Delhi, India, Irrigation Water Quality in Areas Adjoining River Yamuna At Delhi, India Daniel Shindler, UMDNJ, New Brunswick, New Jersey, Methemoglobinemia Slobodan P. Simonovic, The University of Western Ontario, London, Ontario, Canada, Water Resources Systems Analysis, Fuzzy Criteria for Water Resources Systems Performance Evaluation, Participatory Multicriteria Flood Management Shahnawaz Sinha, Malcolm Pirnie Inc., Phoenix, Arizona, Disinfection By-Product Precursor Removal from Natural Waters Joseph P. Skorupa, U.S. Fish and Wildlife Service, Remediation and Bioremediation of Selenium-Contaminated Waters Roel Smolders, University of Antwerp, Antwerp, Belgium, Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs Jinsik Sohn, Kookmin University, Seoul, Korea, Disinfection By-Product Precursor Removal from Natural Waters Fiona Stainsby, Napier University, Edinburgh, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Ross A. Steenson, Geomatrix, Oakland, California, Land Use Effects on Water Quality Leonard I. Sweet, Engineering Labs Inc., Canton, Michigan, Application of the Precautionary Principle to Water Science

xiv

CONTRIBUTORS

Kenneth K. Tanji, University of California, Davis, California, Eh Ralph J. Tella, Lord Associates, Inc., Norwood, Massachusetts, Overview of Analytical Methods of Water Analyses With Specific Reference to EPA Methods for Priority Pollutant Analysis William E. Templin, U.S. Geological Survey, Sacramento, California, California—Continually the Nation’s Leader in Water Use Rita Triebskorn, Steinbeis-Transfer Center for Ecotoxicology and Ecophysiology, Rottenburg, Germany, Biomarkers, Bioindicators, and the Trondheim Biomonitoring System Nirit Ulitzur, Checklight Ltd., Tivon, Israel, Use of Luminescent Bacteria and the Lux Genes For Determination of Water Quality Shimon Ulitzur, Technion Institute of Technology, Haifa, Israel, Use of Luminescent Bacteria and the Lux Genes For Determination of Water Quality U.S. Environmental Protection Agency, How We Use Water in These United States U.S. Agency for International Development (USAID), Water and Coastal Resources U.S. Geological Survey, Water Quality, Water Science Glossary of Terms G. van der velde, Radboud University Nijmegen, Toernooiveld, Nijmegen, The Netherlands, Dose-Response of Mussels to Chlorine F.N.A.M. van pelt, Environmental Research Institute, University College Cork, Ireland, Development and Application of Sediment Toxicity Tests for Regulatory Purposes D.V. Vayenas, University of Ioannina, Agrinio, Greece, Cartridge Filters for Iron Removal Raghuraman Venkatapathy, Oak Ridge Institute for Science and Education, Cincinnati, Ohio, Alternative Disinfection Practices and Future Directions for Disinfection By-Product Minimization, Chlorination ByProducts V.P. Venugopalan, BARC Facilities, Kalpakkam, India, Dose-Response of Mussels to Chlorine Jos P.M. Vink, Institute for Inland Water Management and Waste Water Treatment–RIZA, Lelystad, The Netherlands, Heavy Metal Uptake Rates Among Sediment Dwelling Organisms, SOFIE: An Optimized Approach for Exposure Tests and Sediment Assays Judith Voets, University of Antwerp, Antwerp, Belgium, Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs Mark J. Walker, University of Nevada, Reno, Nevada, Water Related Diseases William R. Walker, Virginia Water Resources Research Center, Management of Water Resources for Drought Conditions Xinhao Wang, University of Cincinnati, Cincinnati, Ohio, Quality of Water Supplies Corinna Watt, University of Alberta, Edmonton, Alberta, Canada, Arsenic Compounds in Water

Janice Weihe, American Water, Belleville, Illinois, Understanding Escherichia Coli O157:H7 and the Need for Rapid Detection in Water June M. Weintraub, City and County of San Francisco Department of Public Health, San Francisco, California, Chlorination By-Products, Alternative Disinfection Practices and Future Directions for Disinfection By-Product Minimization Victor Wepener, Rand Afrikaans University, Auckland Park, South Africa, Active Biomonitoring (ABM) by Translocation of Bivalve Molluscs ˚ Wernersson, GS Development AB, Malm¨o, Sweden, DishwashEva Stahl ing Water Quality Properties Andrew Whiteley, Centre for Ecology and Hydrology–Oxford, Oxford, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Siouxsie Wiles, Imperial College London, London, United Kingdom, Bioluminescent Biosensors for Toxicity Testing Thomas M. Williams, Baruch Institute of Coastal Ecology and Forest Science, Georgetown, South Carolina, Water Quality Management in a Forested Landscape Parley V. Winger, University of Georgia, Atlanta, Georgia, Water Assessment and Criteria M.H. Wong, Hong Kong Baptist University, Kowloon, Hong Kong, Algal Toxins in Water R.N.S. Wong, Hong Kong Baptist University, Kowloon, Hong Kong, Algal Toxins in Water J. Michael Wright, Harvard School of Public Health, Boston, Massachusetts, Alternative Disinfection Practices and Future Directions for Disinfection By-Product Minimization Gary P. Yakub, Kathleen Stadterman-Knauer Allegheny County Sanitary Authority, Pittsburgh, Pennsylvania, Indicator Organisms Yeomin Yoon, Northwestern University, Evanston, Illinois, Disinfection By-Product Precursor Removal from Natural Waters M.E. Young, Conwy, United Kingdom, Water Resources Challenges in the Arab World Mehmet Ali Yurdusev, Celal Bayar University, Manisa, Turkey, Integration of Environmental Impacts into Water Resources Planning Karl Erik Zachariassen, Norwegian University of Science and Technology, Trondheim, Norway, Physiological Biomarkers and the Trondheim Biomonitoring System Luke R. Zappia, CSIRO Land and Water, Floreat, Australia, Microbial Activities Management Harry X. Zhang, Parsons Corporation, Fairfax, Virginia, Water Quality Management and Nonpoint Source Control, Water Quality Models for Developing Soil Management Practices Igor S. Zonn, Lessons from the Rising Caspian A.I. Zouboulis, Aristotle University of Thessaloniki, Thessaloniki, Greece, Biosorption of Toxic Metals, Arsenic Health Effects

WATER QUALITY CONTROL acidity. Under evaporative conditions, FeSO4 and other Fe sulfates can precipitate to form stored acidity. Acid generation is dependent on a large number of factors, including the pH of the environment, temperature, the surface area of the pyrite or other source, the atomic structure of the pyrite, bacterial activities, and oxygen availability. Oxidation of Fe2+ (Eq. 2) is relatively slow at pH below about 5. However, certain bacteria, such as Thiobacillus ferrooxidans, can catalyze the oxidation reaction under acid conditions. Bacterial action increases the reaction rate by a factor of about 106 (7). In addition, Fe3+ , the most effective oxidant via Eq. 4, has negligible solubility above about pH 3.5. As a result of these effects, severe AMD only develops in conditions where the water in contact with pyrite is highly acid and Fe-oxidizing bacteria are present (8). At higher pH, acid generation is relatively slow. During natural weathering of pyrite-bearing rocks, the oxidation reactions happen slowly. In contrast, mining and other rock disturbances, such as road building, can result in greatly increased exposure of pyrite to oxidizing conditions, with resulting rapid acid generation. The water flowing from many underground mines is deficient in oxygen, and the above sequence proceeds only as far as reaction (1) [or perhaps reactions (1), (2) and (4)]. As a result, outflowing water contains elevated Fe2+ that oxidizes after it reaches the surface and generates additional acid owing to Fe precipitation after exposure to air. In such cases, pH can decrease downstream.

ACID MINE DRAINAGE—EXTENT AND CHARACTER ARTHUR W. ROSE Pennsylvania State University University Park, Pennsylvania

Acid mine drainage (AMD), also known as acid rock drainage (ARD), is an extensive environmental problem in areas of coal and metal mining. For example, the Appalachian Regional Commission (1) estimated that 5700 miles of streams in eight Appalachian states were seriously polluted by AMD. AMD is also serious near major metal mining districts such as Iron Mountain, CA and Summitville, CO (2,3). In streams affected by AMD, fish and stream biota are severely impacted and the waters are not usable for drinking or for many industrial purposes (4). In addition to deleterious effects of dissolved constituents (H+ , Fe, Al) on stream life, Fe and Al precipitates can cover the stream bed and inhibit stream life, and suspended precipitates can make the water unusable. In metal mining areas, heavy metals can add toxicity. General references on chemistry of AMD are Rose and Cravotta (5) and Nordstrom and Alpers (6). CHEMISTRY OF FORMATION AMD is formed by weathering of pyrite (FeS2 , iron sulfide) and other sulfide minerals, including marcasite (another form of FeS2 ), pyrrhotite (Fe1−x S), chalcopyrite (CuFeS2 ), and arsenopyrite (FeAsS). The following reactions, involving oxygen as the oxidant, occur when pyrite is exposed to air and water: FeS2 + 3.5O2 + H2 O = Fe 2+

Fe

+

+ 0.25O2 + H = Fe Fe

3+

2−

2+

+ 2SO4

3+

+ 0.5H2 O

+

+ 2H

+

+ 3H2 O = Fe(OH)3 + 3H

CHEMISTRY OF ACID MINE DRAINAGE The H+ generated by pyrite oxidation attacks various rock minerals, such as carbonates, silicates, and oxides, consuming some H+ and releasing cations. For this reason, AMD commonly contains moderate to high levels of Ca, Mg, K, Al, Mn, and other cations balancing SO4 , the dominant anion. These reactions consume H+ and increase the pH. If reaction with rock minerals is extensive, the resulting water may have a pH of 6 or even higher, and if oxidizing conditions exist, Fe may be relatively low. If carbonates are present in the affected rocks, the ‘‘AMD’’ may contain significant alkalinity as HCO3 . AMD is characterized by SO4 2− as the dominant anion but can have a wide range of pH, Fe, and other cations (Table 1). The pH of AMD typically ranges from about 2.5 to 7, but the frequency distribution of pH is bimodal, with most common values in the range 2.5 to 4 and 5.5 to 6.5 (5). Relatively fewer values are in the range 4 to 5.5. An extreme value of negative 3.6 is reported (2). Common ranges of other constituents are up to 100 mg/L Fe, up to 50 mg/L Al, up to 140 mg/L Mn, and up to 4000 mg/L SO4 . A key variable characterizing AMD is ‘‘acidity.’’ Acidity is commonly expressed as the quantity of CaCO3 required to neutralize the sample to a pH of 8.3 by reaction (8). The acidity includes the generation of H+ by reactions (1) and (3), as well as the effects of other cations that generate

(1) (2) (3)

The sum of these, representing complete oxidation and Fe precipitation, is FeS2 + 3.75O2 + 3.5H2 O = Fe(OH)3 (s) + 2SO4 2− + 4H+ (4) In addition, the Fe3+ formed in Eq. 2 is a very effective oxidant of pyrite: FeS2 + 14Fe3+ + 8H2 O = 15Fe2+ + 2SO4 2− + 16H+

(5)

These reactions also generate considerable heat, which tends to increase temperature and reaction rate. In the above equations, the Fe precipitate is shown as Fe(OH)3 , but other ferric Fe phases can precipitate, depending on the conditions. Goethite (FeOOH), hematite (Fe2 O3 ), ferrihydrite (Fe5 HO8 ·4H2 O), schwertmannite (Fe8 O8 (OH)6 (SO4 )), and jarosite (KFe3 (SO4 )2 (OH)6 ) are among the products. The latter two products represent ‘‘stored acidity’’ that can react further to release additional 1

2

THE CONTROL OF ALGAL POPULATIONS IN EUTROPHIC WATER BODIES Table 1. Analyses of Typical ‘‘Acid Mine Drainage’’ (5)

Constituent

Units

WMB A1

WMS 2K

LMS S2-15

pH Acidity Alkalinity Fe Mn Al Ca Mg SO4 Spec. Cond.

mg/L CaCO3 mg/L CaCO3 mg/L mg/L mg/L mg/L mg/L mg/L µS/cm

2.6 688 0 174 25.5 68.9 83 74 913 2120

4.2 270 0 34 67 26 270 280 1600 1860

6.9 0 730 5.7 7.5 10,000 (road salt)

Benbow and Merritt (24)

a When Cl− or road salt was used instead of NaCl in a study, it is indicated in parentheses. Source: The table is modified and expanded from Blasius and Merritt (7).

(7) (7) (7) (7)

ROAD SALT

organisms die. In sublethal tests, the EC50 is reported, which is defined as the effective concentration where the tested variable (e.g., number of eggs or growth rate) is reduced by 50%. We provide Table 3 as a summary of tolerance levels of macroinvertebrates reported in the literature. This table was modified and expanded from Blasius and Merritt (7). From the literature in Table 3, it is apparent that salt tolerance for aquatic macroinvertebrates is relatively high, with highest acute toxicity reported from mayflies (Ephemeroptera: Hexagenia limbata). Acute toxicity studies reported LC50 values (or greater mortality) from 2400 to >13,000 mg/L NaCl (or road salt). Variable mortality was evident among taxa with Culex mosquitoes (Culicidae) having an LC50 of 10,254 mg/L NaCl and caddisfly (Trichoptera) taxa with values from 3526 to 13,308. Nonlethal effects also were variable. Drift effects for various taxa (amphipods, caddisflies, mayflies, stoneflies, and craneflies) ranged from 2500 to 10,000 mg/L NaCl, with some drift effects found at concentrations >1000 mg/L NaCl. Growth rates for a mayfly (H. limbata) did not differ among treatments from 0–8000 mg/L NaCl; however, osmoregulation was lost at higher concentrations. This variation in lethal and nonlethal road salt tolerance may be a product of artificial testing conditions that do not represent natural environmental changes in temperature and other variables. In addition, many taxonomic groups have not been tested, indicating that unstudied, yet sensitive species may exist. Most studies did not evaluate the background chloride levels of waterbodies typically occupied by the invertebrates tested, and when background chloride levels were measured, they were often below the invertebrate toxicity levels. In several studies, it was noted that chloride levels were sometimes diluted with snow melt runoff at the time of the highest expected impact (early spring). Nonlethal effects (e.g., drift, fecundity, production) have been understudied and may be important to invertebrates impacted by residual road salt runoff. Additional data and studies can be found in the review by Environment Canada (4). EFFECTS ON ZOOPLANKTON AND FISH Road salt tolerance variability has been reported for several species of zooplankton, with Daphnia pulex, D. magna, and Ceriodaphnia dubia being the most commonly tested taxa (4). Results from short-term acute toxicity studies (≤24 to 96 h) reported LC50 values ranging from 2308 to 7754 mg/L NaCl (4). In studies lasting 7–10 d, LC50 values ranged from about 2000 to 6000 mg/L NaCl, whereas EC50 for zooplankton mean brood size, number of broods, or total progeny ranged from about 1400 to 6000 mg/L NaCl (4). Fish road salt toxicity was low during studies 7000 mg/L NaCl for bluegill (Lepomis macrochirus), indian carp fry (Cirrhinius mrigalo, Labeo rohoto, and Catla catla), brook trout (Salvelinus fontinalis), and rainbow trout (Oncorhynchus

323

mykiss) (4). Longer acute toxicity studies reported LC50 values for bluegill, rainbow trout, and indian carp fry to be >9500, 11,112, and 4980 mg/L NaCl, respectively (4). The American eel (Anguilla rostrata) was reported to have LC50 values from about 18,000 to 22,000 mg/L NaCl in one study, and fathead minnow (Pimephales promelas) values were from >7500 to 10,831 mg/L NaCl (4). In seven to ten day acute toxicity studies on fathead minnow and frog (Xenopus laevis) embryos, eggs, and larvae, LC50 values ranged from 1440 to 5490 mg/L NaCl depending on life stage (4). CONCLUSIONS The sustained and increasing use of road salt for winter roadway maintenance is becoming a popular issue as a result of raised awareness of potential ecological effects on natural waterways. Balancing human transportation safety with potential ecological repercussions drives this issue, and it is clear from the literature that the answer will be complicated, if ever resolved. The economics associated with using deicer alternatives suggest that, at present, road salt is the best practical agent for winter snow and ice removal. Chlorides are known to have effects on organisms in nature, and in many reports, it is evident that chloride concentrations are rising in waterbodies associated with roadways that are heavily treated with road salt. However, short-term toxicity studies have shown that mortality among aquatic zooplankton, macroinvertebrates, and fish is highly variable, speciesdependent, and related to test conditions. Many toxicity studies are done under laboratory conditions that are far removed from the natural variation of climatic and biological components of natural waterbodies, which may influence true mortality of certain taxa. Apart from toxicity studies, larger scale studies that evaluate complex community and ecosystem level responses are needed for a better understanding of road salt effects in nature. BIBLIOGRAPHY 1. D’Itri, F.M. (1992). Chemical Deicers and the Environment. Lewis Publishers, Chelsea, MI. 2. Salt Institute. (2000). Deicing salt facts: a quick reference. SI Pub. 2(77): 83. 3. Field, R. and O’Shea, M.L. (1992). The USEPA research program on the environmental impacts and control of highway deicing salt pollution. In: Chemical Deicers and the Environment. F.M. D’Itri (Ed.). Lewis Publishers, Chelsea, MI, pp. 117–133. 4. Environment Canada. (2001). Priority Substances List Assessment Report—Road Salts. 5. Environmental Protection Agency. (2003). Administrative Determination: EPA Clarifies that Ferric Ferrocyanide is one of the ‘‘Cyanides’’ in the Clean Water Act’s List of Toxic Pollutants. Environmental Protection Agency, Washington, DC, EPA-821-F-03-012. 6. Salt Institute. (2004). Highway Salt and our Environment. Salt Institute, Alexandria, VA. 7. Blasius, B.J. and Merritt, R.W. (2002). Field and laboratory investigations on the effects of road salt (NaCl) on

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8. Molles, M.C. Jr. (1980). Effects of Road Salting on Aquatic Invertebrate Communities. U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO, p. 10. 9. Scott, W.S. (1976). The effect of road deicing salts on sodium concentration in an urban water-course. Environ. Pollut. 10: 141–153. 10. Williams, D.D., Williams, N.E., and Cao, Y. (2000). Road salt contamination of groundwater in a major metropolitan area and development of a biological index to monitor its impact. Water Res. 34(1): 127–138. 11. Scott, W.S. (1980). Road salt movement into two Toronto streams. J. Environ. Eng. Div. 12. Struzeski, E. (1971). Environmental Impact of Highway Deicing. United States Environmental Protection Agency, Washington, DC. 13. Morin, D. and Perchanok, M. (2000). Road Salt Loadings in Canada. Supporting Document for the Road Salt PSL Assessment. Commercial Chemicals and Evaluation Branch, Environment Canada, Hull, Quebec. 14. United States Environmental Protection Agency. (1994). National Water Quality Inventory: 1992. U.S. EPA, Washington DC. 15. Bubeck, R.C. et al. (1971). Runoff of deicing salt: effects on Irondequoit Bay, Rochester, New York. Science 172(3988): 1128–1132. 16. Peters, N.E. and Turk, J.T. (1981). Increases in sodium and chloride in the Mohawk River, New York, from the 1950s to the 1970s attributed to road salt. Water Res. Bull. 17(4): 586–598. 17. Mayer, T., Snodgrass, W.J., and Morin, D. (1999). Spatial characterization of the occurrence of road salts and their environmental concentrations as chlorides in Canadian surface waters and benthic sediments. Water Qual. Res. 34(4): 545–574. 18. Environment Canada (2001). Priority Substances List Assessment Report—Road Salts. Environment Canada, Hull, Quebec. 19. Judd, J.H. (1970). Lake stratification caused by runoff from street deicing. Water Res. 4: 521–532. 20. Lathrop, R.C. (1975). A Limnological Study of Two Neighboring Lakes: First Sister Lake and Second Sister Lake, Washtenaw County, Michigan [MS]. Natural Resources, The University of Michigan, Ann Arbor, MI. 21. Emmett, W.W. (1975). The Channels and Waters of Upper Salmon River, Idaho. U.S. Department of Interior, Washington, DC. 22. Drever, J.I. (1982). The Geochemistry of Natural Waters. Prentice Hall, Englewood Cliffs, NJ. 23. Wilcox, D.A. (1986). The effects of deicing salts on water chemistry in Pinhook Bog, Indiana. Water Res. Bull. 22(1): 57–65. 24. Benbow, M.E. and Merritt, R.W. (2004). Road-salt toxicity of select Michigan wetland macroinvertebrates under different testing conditions. Wetlands 24(1): 68–76. 25. Ohno, T. (1990). Levels of cyanide and NaCl in surface waters adjacent to road salt facilities. Environ. Pollut. 67: 123–132. 26. Demers, C.L. (1997). Effects of road deicing salt on aquatic invertebrates in four Adirondack streams. In: Chemical Deicers and the Environment. F.M. D’Itri (Ed.). Lewis Publishers, Ann Arbor, MI, pp. 245–251.

27. Crowther, R.A. and Hynes, H.B.N. (1977). The effect of road deicing salt on the drift of stream benthos. Environ. Pollut. 14: 113–126. 28. Hsu, M. (1984). Anticaking Agents in Deicing Salt. Materials and Research Division, Maine Department of Transportation, p. 84–4. 29. Doner, H.E. (1978). Chloride as a factor in mobilities of Ni(II), Cu(II), and Cd(II) in soil. Soil Sci. Soc. Am. J. 42: 882–885. 30. Jones, P.H., Jeffrey, B.A., Watler, P.K., and Hutchon, H. (1992). Environmental impact of road salting. In: Chemical Deicers and the Environment. F.M. D’Itri (Ed.). Lewis Publishers, Chelsea, MI, pp. 1–116. 31. Shanley, J.B. (1994). Effects of ion exchange on stream solute fluxes in a basin receiving highway deicing salts. J. Environ. Qual. 23: 977–986. 32. Wang, J.S., Huang, P.M., Liaw, W.K., and Hammer, U.T. (1991). Kinetics of the desorption of mercury from selected freshwater sediments as influenced by chloride. Water Air Soil Poll. 56: 533–542. 33. Macleod, C.L., Borcsik, M.P., and Jaffe, P.R. (1996). Effect of infiltrating solutions on the desorption of mercury from aquifer sediments. Environ. Technol. 17: 465–475. 34. Norton, S.A., Henriksen, A., Wright, R.F., and Brakke, D.F. (1987). Episodes of natural acidification of surface waters by natural sea salts. In: Geomon, Int. Workshop on Geochemistry and Monitoring in Representative Basins´oExtended Abstracts. B. Moldan and T. Paces (Eds.). Geological Survey, Prague, Czechoslovakia, pp. 148–150. 35. Hoffman, R.W., Goldman, G.R., Paulson, S., and Winters, G.R. (1981). Aquatic impacts of deicing salts in the Central Sierra Nevada Mountains, California. Water Res. Bull. 17(2): 280–285. 36. Kjensmo, J. (1997). The influence of road salts on the salinity and the meromictic stability of Lake Svinsjoen, southeastern Norway. Hydrobiologia. 347: 151–158. 37. Sharp, R.W. (1971). Road Salt as a Polluting Element. State University College of Forestry at Syracuse University, Syracuse, NY. 38. Shapiro, J., Chamberlain, W., and Barrett, J. (1969). Factors influencing phosphate use by algae. Paper presented at Proc. 4th Int. Conf. Wat. Pollut. Res. Prague. 39. Cherkauer, D.S. and Ostenso, N.A. (1976). The effect of salt on small, artificial lakes. Water Res. Bull. 12(6): 1259–1267. 40. Rosenberg, D.M. and Resh, V.H. (1993). Freshwater Biomonitoring and Benthic Macroinvertebrates. Chapman and Hall, New York. 41. Merritt, R.W. and Cummins, K.W. (Eds.). (1996). An Introduction to the Aquatic Insects of North America, 3rd Edn. Kendall/Hunt, Dubuque, IA. 42. Williams, D.D., Williams, N.E., and Cao, Y. (1997). Spatial differences in macroinvertebrate community structure in springs in southeastern Ontario in relation to their chemical and physical environments. Can. J. Zool. 75: 1404–1414. 43. Williams, D.D. and Williams, N.E. (1998). Seasonal variation, export dynamics and consumption of freshwater invertebrates in an estuarine environment. Estuarine, Coastal Shelf Sci. 46: 393–410. 44. Williams, D.D. and Williams, N.E. (1998). Aquatic insects in an estuarine environment: densities, distribution and salinity tolerance. Freshwater Biol. 39: 411–421. 45. Giberson, D.J., Bilyj, B., and Burgess, N. (2001). Species diversity and emergence patterns of Nematocerous flies (Insecta: Diptera) from three coastal salt marshes in Prince Edward Island, Canada. Estuaries 24: 862–874.

REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS 46. Williams, D.D. (2003). The brackishwater hyporheic zone: invertebrate community structure across a novel ecotone. Hydrobiologia 510: 153–173. 47. Thornton, K.W. and Sauer, J.R. (1972). Physiological effects of NaCl on Chironomus attenuatus (Diptera: Chironomidae). Ann. Entomol. Soc. Am. 65(4): 872–875. 48. Sutcliffe, D.W. (1961). Studies on salt and water balance in caddis larvae (Trichoptera): I. Osmotic and ionic regulation of body fluids in Limnephilus affinis Curtis. J. Exp. Biol. 38: 501–519. 49. Sutcliffe, D.W. (1961). Studies on salt and water balance in caddis larvae (Trichoptera): II. Osmotic and ionic regulation of body fluids in Limnephilus stigma Curtis and Anabolia nervosa Leach. J. Exp. Biol. 38: 521–530. 50. Dowden, B.F. and Bennett, H.J. (1965). Toxicity of selected chemicals to certain animals. J. Water Pollut. Control Fed. 37: 1308–1316. 51. Hamilton, R.W., Buttner, J.K., and Brunetti, R.G. (1975). Lethal levels of sodium chloride and potassium chloride for an oligochaete, a chironomid midge, and a caddisfly of Lake Michigan. Environ. Entomol. 4(6): 1003–1006. 52. Kersey, K. (1981). Laboratory and Field Studies on the Effects of Road De-icing Salt on Stream Invertebrates. University of Toronto, Institute for Environmental Studies, Snow and Ice Control Working Group, Toronto, Canada, SIC-9. 53. Chadwick, M.A.J. (1997). Influences of Seasonal Salinity and Temperature on Hexagenia limbata (Serville) (Ephemeroptera: Ephemeridae) in the Mobile River. Masters Thesis. Auburn University, Auburn, AL. 54. Goetsch, P.-A. and Palmer, C.G. (1997). Salinity tolerances of selected macroinvertebrates of the Sabie River, Kruger National Park, South Africa. Arch. Environ. Contam. Toxicol. 32: 32–41. 55. Kundman, J.M. (1998). The Effects of Road Salt Runoff (NaCl) on Caddisfly (Hydropsyche betteni) Drift in Mill Run, Meadville, Pennsylvania. Senior Thesis. Department of Environmental Science, Allegheny College, Meadville, PA. 56. Chadwick, M.A., Hunter, H., Feminella, J.W., and Henry, R.P. (2002). Salt and water balance in Hexagenia limbata (Ephemeroptera: Ephemeridae) when exposed to brackish water. Florida Entomol. 85(4): 650–651.

REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS ANNE NG B.J.C. PERERA Swinburne University of Technology Hawthorne, Victoria, Australia

INTRODUCTION Rivers supply valuable water resources for humans, and many aquatic ecosystems. However, due to population increase and its adverse effects on the rivers, and other adverse activities, the water quality in rivers has generally declined. Therefore, appropriate river water quality management strategies aimed at controlling and improving water quality should be seriously considered. To manage river water quality in the most effective

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and efficient way, the cause and effect relationships of the river system must first be investigated. River water quality modeling tools are extensively used in water quality management to identify these cause and effect relationships. River water quality modeling software is designed to model the water quality in a river system. Many generic water quality modeling software tools are widely available, and most of them are in the public domain and available at no cost. The applicability of these software tools depends on the study objectives. Therefore, it is necessary to review available water quality software modeling tools, so that the most appropriate software tool can be selected for the specific application. Here, we mainly concentrate on reviewing available public domain river water quality modeling software tools, although a brief review of catchment water quality modeling software tools is also presented. A case study is also included to identify and select the most suitable software for modeling of water quality in the Yarra River, Australia. WATER QUALITY MODELING SOFTWARE TOOLS In general, the water quality modeling software tools can be categorized into three broad groups, namely, catchment, river, and integrated software tools. Under these groups, the available public domain software is shown in Fig. 1. Since the focus here is on river water quality software tools, they are further divided into two groups, namely, steady and unsteady state modeling software tools. Catchment Water Quality Modeling Softwares Catchment water quality modeling software tools are used to estimate the amount of pollutant loadings generated from different land surfaces in catchments, which affects the water quality in streams and rivers. A listing of commonly used catchment water quality modeling software is shown in Fig. 1. The most commonly used catchment water quality modeling software is the Agricultural Nonpoint Source Pollution Software (AGNPS) (1), which was developed by the United States Agricultural Research Services. AGNPS can be used in both event and continuous simulation modes, to estimate sediment and nutrient loads from agricultural areas. The catchment is divided into a number of cells to determine pollutant loadings. Tim et al. (2) used AGNPS (linked with a GIS system) to examine the effect of varying widths of vegetated buffer strips on sediment yield of the bluegrass catchment in Iowa, USA. AGNPS was also used to predict pollutants generated from site-specific catchment characteristics in Missouri, USA (3) Storm Water Management Model (SWMM) is an urban stormwater quantity and quality software tool that was developed by the United States Environmental Protection Agency (U.S. EPA) (4), which can be used in both event and continuous simulation modes. Data required by SWMM are relatively intensive. It has the most versatile hydrological and hydraulic simulation modules, while the water quality simulation is relatively weak

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REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS Water quality modelling software

Catchment

Figure 1. Summary of available public domain water quality software.

• AGNPS • SWMM • HSPF

River water quality

Integrated

Steady state

Unsteady state

• QUAL2E • EXAMSII • SYMTOX4

• WASP5 • CE-QUAL-RIV1 • CE-QUAL-W2

in representation of the true physical, biological, and chemical processes (5). The Hydrological Simulation Program–FORTRAN (HSPF) is one of the comprehensive software tools, which simulates the catchment runoff processes together with a minor component on river water quality (6). This software tool can be used to simulate nonpoint source runoff. Major conventional water quality constituents such as dissolved oxygen (DO), biochemical oxygen demand (BOD), and all forms of nitrogen and phosphorus can be simulated. As discussed in References 5 and 7, HSPF is a highly complex software tool, which requires extensive resources and data. Moore et al. (8) used HSPF on the North Reelfoot Creek catchment, located in the northwest corner of Tennessee, USA to examine several best management practices in reducing erosion and sedimentation. Runoff and sediment load in the Upper Changjiang River Basin in China was simulated using HSPF (9). They found that HSPF underestimated the suspended solid concentration by up to 72% of the actual. The error in the model may have resulted from lack of data to produce a wellcalibrated model. River Water Quality Modeling Software Tools River water modeling software tools are used to simulate the effects of pollutants generated from catchment and point sources (stormwater/treated sewage discharge outfall), on river and stream water quality. They do not estimate the nonpoint source pollutant load from the catchments. This category is reviewed in detail, since the focus is on review of river water quality modeling software tools. Two types of software tools exist, namely, steady and unsteady state. Steady-State Software Tools. The steady-state river water quality modeling software assumes that the magnitude of flow and pollutant entering the stream do not vary with time (10). Therefore, in these software, the ‘‘average’’ inputs of flows and pollutants are considered for the flow event, giving ‘‘average’’ values for output water quality concentrations. Although these software tools cannot assess the water quality for time varying conditions, they can be useful in determining the critical water quality concentrations under design conditions. The results obtained from steady-state software are always more conservative than the results obtained with the unsteady-state software (11). The steady-state software

• • • •

BASINS DESERT StreamPlan WATERSHEDSS

tools are commonly used because they are less complex, easy to use, and require less input data. Below is a review of some commonly used public domain steadystate river water quality modeling software tools and their applications. The Enhanced Stream Water Quality Model (QUAL2E) is a one-dimensional steady-state river water quality simulation software tool, which was developed and is supported by U.S. EPA (12). In 1995, QUAL2E was upgraded with a Windows interface to enhance its user-friendliness. Although QUAL2E is a steady-state flow software tool, it can also account for diurnal variation (difference in temperature between the warmest and coolest parts of the day) in temperature or algal photosynthesis and respiration. QUAL2E can model all conventional water quality constituents, as well as three other user-defined water quality constituents. QUAL2E can be applied to different waterbody types and allows modeling of multiple waste discharges and diversions. It also includes components that allow implementation of uncertainty analysis of model parameters using first-order error analysis, one-at-a-time, and Monte Carlo simulation (see UNCERTAINTY ANALYSIS IN WATERSHED MODELING in this encyclopedia). QUAL2E has been extensively used in many applications. The majority of these applications used this software tool to simulate major conventional water quality constituents in rivers. Some recent applications on modeling conventional water quality constituents in rivers include the work of Ghosh and McBean (13), Cvitanic and Kompare (14), and Ning et al. (15). In comparison, limited applications were cited in the literature using QUAL2E to simulate microbial water quality (16). Ghosh and McBean (13) used QUAL2E to develop a water quality model of the Kali River in India. Although they experienced data limitations in their application, they commented that provided adequate data were available, QUAL2E can be effectively used to model water quality in rivers that have water pollution problems. This is consistent with the findings of Barnwell et al. (17), who stated that it is important to have site-specific data representing the properties of the actual system to model river water quality successfully. Cvitanic and Kompare (14) applied QUAL2E to simulate and predict the possible changes in water quality in the River Sava in Croatia with the construction of impoundments. However, they found that QUAL2E was

REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS

not suitable for their application, because the model prediction could not be validated during the validation stage. They concluded that a two-dimensional model is more suitable to predict water quality in impoundments, since large variations of river water quality exist in the river (laterally and vertically) during summer periods. They could have simply avoided this problem by selecting the most suitable software tool for their study, since they had a good prior knowledge of lateral and vertical water quality variations of the river. Ning et al. (15) developed and calibrated a model for the Kao-Ping River Basin in Taiwan using QUAL2E. They successfully used the model as a simulation tool to assess the water quality standard requirements downstream by hypothetically eliminating pig farming activities and constructing a sewer system in the upstream areas. Although QUAL2E has been successfully used as a simulation tool in this study, they commented that an economic instrument for controlling and reducing the wasteload allocations would also be needed in the long term. Steynberg et al. (16) used QUAL2E in an effort to simulate the effect of various management strategies, which can result in the desired level of fecal coliform in the Rietspruit catchment in South Africa. It was found that the model was unsuccessful in predicting the measured fecal coliform level. Due to the time varying discharge of effluent and different levels of wastewater treatment, the use of the steady-state model QUAL2E was inadequate for their study. Reviewing the river water quality modeling software, Shanahan et al. (18) reported that QUAL2E has become the standard modeling software tool and has shown to be most applicable in situations where point source pollutants are dominant. Therefore, QUAL2E has been integrated and linked into a number of other modeling software tools. For example, QUAL2E has been integrated into decision support systems (DSSs), as in BASIN (5). Mulligan and Brown (19) and Ng (20) linked QUAL2E with genetic algorithm optimization software, GENESIS (21). As stated in Yang et al. (22), the use of remotely sensed water quality data with QUAL2E in the Te-Chi Reservoir in Taiwan can accurately interpret the spatial variation in water quality and monitor the water quality. De Azevedo et al. (23) linked QUAL2E with a water quantity network flow allocation model MODSIM of Labadie (24) to assess and evaluate six management alternatives for strategic river basin planning. Exposure Analysis Modelling System (EXAMSII) (25) can be used in modeling of streams, rivers, and reservoirs in one-, two-, and three-dimensional modes. It accounts for many water quality transformation processes, such as photolysis, hydrolysis, oxidation, and sorption with sediments and biota (5). SYMTOX4, the Simplified Method Program–Variable Complexity Stream Toxics Model (26), is a one-dimensional software tool that can be used to simulate the water column and benthic toxicity caused by point sources discharged into rivers. Major conventional water quality constituents can be simulated using SMYTOX4. This software is Windows based and has the capability to perform

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uncertainty and sensitivity analyses. One example was citied in Reference 5 using SMPTOX 4 on the Flint River, Michigan, in the United States. Unsteady-State Software Tools. Unsteady-state (or dynamic) water quality software tools can be used to simulate water quality response in rivers whose flow and water quality characteristics change with time. All natural rivers and streams have unsteady-state flow characteristics, especially during high flow period, and therefore unsteady-state modeling software tools are more realistic. However, they require more data inputs compared to steady-state software tools. Below is a review of the available public domain unsteady-state water quality software tools (which are also listed in Fig. 1), together with their applications. Water Quality Analysis Simulation Program (WASP5) is a well-known unsteady-state water quality simulation software tool supported by U.S. EPA (27). This software has flexible compartments such as hydrodynamics, eutrophication (DO/nutrients/algal/carbon), and toxins. The user can use these compartments selectively or all compartments simultaneously. This software tool can be used to model rivers and streams in one-, two-, and threedimensional modes. Lung and Larson (28) successfully used WASP5 to predict the impact of eutrophication under steady state in the Upper Mississippi River and Lake Pepin in the United States. They recognized that the unsteady-state mode should be used to study algal growth; however, relevant data inputs for algal growth dynamics were not available to them for unsteady-state flow modeling. They justified the use of steady-state mode after ascertaining that the phytoplankton population did not vary greatly from hour to hour. ´ Suarez et al. (29) developed an unsteady-state water quality model of the Nal´on River in Spain using WASP5. This model was used to assess the impact of combined sewer flow (with daily fluctuations) on river quality and its effect on the aquatic system. The majority of the water quality related inputs required in WASP5 (e.g., reaeration rate methods, decay rates) were obtained from preliminary water quality modeling using QUAL2E. The WASP5 model was successfully calibrated, which adequately simulated the water quality and activities occurring in the river accounting for time variation. However, the decay rates were required to be the same for all reaches of the river in WASP5, which they found to be one of the main deficiencies. A eutrophication model was developed for the Tolo Harbour in Hong Kong using WASP5 by Lee and Arega (30). This model accounts for sediment water interaction together with time and spatial variation in water quality. They successfully simulated DO and chlorophyll-a concentrations and matched them with observations. The model was developed to study the longterm trends of eutrophication in the harbor. As reported by the World Bank (31), WASP5 is not appropriate for basins with large catchment areas, since it is complex and time consuming to calibrate and simulate water quality conditions of rivers and streams associated with these large basins.

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REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS

The Hydrodynamic and Water Quality Model for Streams (CE-QUAL-RIV1) is a one-dimensional software tool developed by The U.S. Army Experiment Waterways Experiment Station (32). It has two separate compartments: hydrodynamics and water quality. The results obtained from the hydrodynamics compartment are used as input to the water quality compartment. Many conventional water quality constituents can be modeled, including the effects of algae and macrophytes. One advantage of using this model is that it allows modeling of river structures such as dams. This model is less widely used compared to QUAL2E and WASP5 (33). CE-QUAL-RIV1 has been applied to the Cumberland River, the Chattahoochee River, and the lower Ohio River in the United States (5). CE-QUAL-W2, also developed by The U.S. Army Waterways Experiment Station (32), is a two-dimensional experiment, laterally averaged, hydrodynamic and water quality model. It contains one module, which models both hydrodynamics and water quality. It can model DO, nutrients, and algae interactions. Since this software accounts for variations in longitudinal and vertical directions (not in lateral direction), this software is best used in situations where large variations in lateral velocities and water quality concentrations do not occur (5). Martin (34) used CE-QUAL-W2 for DeGray Lake in Arkansas (USA) and demonstrated its usefulness. Integrated Water Quality Modeling Software Tools. The integrated software tools consist of several stand-alone tools in one package. For example, catchment and river modeling software tools can be integrated into one package to analyze both flow and water quality in rivers and associated catchments. When some form of decision support is available in integrated software, they are called decision support systems (DSSs). There is an increased use of DSSs in river water quality management in recent times. The purpose of a DSS is to effectively allow decisionmakers to simulate the whole process of decision-making, related to the particular application (e.g., improving river water quality), to investigate and simulate alternative decision management scenarios, and to improve the effectiveness of decision-making. Below are descriptions of four public domain integrated water quality software tools (or DSSs) found in the literature. Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), developed by the U.S. EPA Office of Water (35), consists of a catchment water quality modeling software tool (NPSM) and a river water quality modeling software tool (QUAL2E). The Nonpoint Source Model (NPSM) is a Windows interface that works with the catchment model HSPF (6). The graphical system in BASINS uses Arc-View GIS software. One disadvantage of this system is that the data management module is less useful to countries other than the United States, since all relevant information and data are only applicable for basins in the United States, which are updated annually. Decision Support System for Evaluating River Basin Strategies (DESERT) is a flexible, Microsoft Windowsbased tool for decision support for water quality management at the catchment scale. DESERT was developed by two organizations jointly: International Institute for

Applied Systems Analysis in Austria (IIASA) and the Institute for Water and Environmental Problems in Russia (36). This software tool provides a powerful instrument for developing least-cost river catchment policies, and for assessing these policies under conditions that are deviating from the design scenario (37). Fan (38) used DESERT to identify the most efficient water quality management strategy in terms of wastewater treatment alternatives for the Veszpr´emi-S´ed River in Budapest, Hungary. StreamPlan (Spreadsheet Tool for River Environmental Assessment Management and Planning) was developed at IIASA in 1996 (39). It is a DSS that allows decisionmakers to evaluate river and catchment water quality policies considering local and regional water quality goals, effluent standards, costs, financing, economic instruments, municipal water management issues, and generation of wastewater treatment plant alternatives. StreamPlan was developed for use on a Microsoft Excel platform, which is familiar to most model users. Jolma et al. (40) discussed the use of StreamPlan in three degraded river catchments in Central and Eastern Europe: Narew (Poland), Morava (The Czech Republic), and Nitra (Slovak Republic). Water, Soil and Hydro-Environmental Decision Support System (WATERSHEDSS) is similar to BASINS, except WATERSHEDSS is more focused on nonpoint source pollution (41). The U.S. EPA Office of Research developed this system in 1994, with the cooperation of North Carolina State University water quality group and the Department of Biological Engineering of Pennsylvania State University (42). EVALUATION AND SELECTION OF WATER QUALITY SOFTWARE FOR THE YARRA RIVER, AUSTRALIA To manage river quality in the most effective and efficient way, the cause and effect relationships of the river system must first be identified. A river water quality modeling tool is required for the Yarra River, Australia, for this purpose mainly to identify the cause and effect relationships in the river from different settings of effluent license limits from sewage treatment plants (STPs). Furthermore, this modeling should be able to simulate and study the effects of various ‘‘what-if’’ management strategies prior to implementation. The catchment water quality software tools mainly deal with the generation and transport of overland pollution and do not directly consider river water quality. Therefore, they are not suitable for modeling Yarra River water quality, although quantifying overland pollutant runoff into streams is an important component in the modeling of river water quality. However, modeling of overland pollutant runoff is outside the scope of modeling in-stream water quality in the Yarra River. The river water quality software tools deal with river water quality and therefore are relevant to modeling water quality in the Yarra River. Although the integrated water quality modeling software (or DSS) tools are very efficient simulation and management systems as complete decision-making tools, they require extensive data, which were not available for the Yarra River at the time of selection of the appropriate modeling tools and, therefore, were not considered. Thus,

REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS

the river water quality software tools were further investigated for modeling the Yarra River, its tributaries, and associated STPs. Four criteria, as listed below, were used in selecting the river water quality software for use in the Yarra River, from the computer software tools listed in Fig. 1. • Data availability for use in the modeling software and the purpose of using the model • Ability to simulate major conventional water quality constituents such as DO, BOD, and nutrients • Ability to produce longitudinal profiles (upstream/ downstream) of water quality concentrations • Wider successful usage of the software These broader criteria will certainly reduce the number of river water quality software tools that can be used for the Yarra River. QUAL2E and WASP5 were the only two software tools that fitted the above criteria and therefore can be used for development of the Yarra River water quality model. Both software tools can simulate

conventional water quality constituents, can produce longitudinal water quality profiles, and have been used successfully on many applications. As stated in References 5 and 18, both QUAL2E and WASP5 software tools are well known and credible, with extensive capabilities and wide usage. These software tools were further evaluated for modeling the Yarra River. A summary of the evaluation results is given in Table 1. Three main categories, namely, fundamentals, water quality, and others, were considered in classifying the attributes of these software tools. Some of these attributes were considered in a comparative study by Ambrose et al. (27). The first category consists of attributes, which forms the basic structural framework of the software tools. Most attributes are self-explanatory. Hydrodynamics is an extremely important attribute in water quality modeling, because the movement of water affects the fate of the water quality constituents. WASP5 has an independent compartment for simulating hydrology of the water body system, whereas QUAL2E requires hydrology (or flows)

Table 1. Evaluation Summary of QUAL2E and WASP5 Attributes Fundamentals Operational requirements

Water body type

Dimension

Transport Hydrodynamics Steady/unsteady Discretization Hydraulic structures Water quality constituents DO

Nitrogen forms

Phosphorus forms

Temperature Settling/benthos Toxicity Others Uncertainty and sensitivity analysis

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Documentation Support Credibility River, stream Estuary Lake Reservoir one Two Three Advection Dispersion Input Simulated Steady state Unsteady state — — Reaeration/(built-in equations) CBOD NH3 NO2 SOD Algae Org-N NH3 NO2 NO3 Algae Org-P Diss–P Algae

QUAL2E

WASP5

Y Y Y Y N N N Y N N Y Y Y N Y N Y Y

Y Y Y Y N Y Y Y Y Y Y Y Y Y Y Y Y N

Y/Y Y Y Y Y Y Y Y Y Y N Y Y Y Y Y/Y N

Y/Y Y Y Y Y Y Y Y N Y Y Y Y Y N Y/Y Y

Y

N

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as input. Both software can be operated in a steady-state environment, which is the most common water quality modeling application, although WASP5 can also be used in an unsteady-state environment. A one-dimensional longitudinal process can be modeled with both software tools and is considered as the dominant transport process in most river systems, since the water quality process in the river is considered well mixed in both lateral and vertical directions (10). WASP5 can simulate river water quality in two and three dimensions. The possible increase in DO concentration by water quality structures such as dams and weirs can only be considered in QUAL2E. The second category is related to water quality constituents. Both software tools account for most sinks on DO processes. Built-in reaeration formulas are available in both QUAL2E and WASP5. QUAL2E accounts for the four forms of nitrogen in the nitrogen cycle: Org-N, NH3 , NO2 , and NO3 (10). WASP5 combines NO2 and NO3 , in the overall nitrification process from NH3 to NO3 . However, as stated in Reference 7, lumping of NO2 and NO3 does not cause any significant effect in the overall result, since the transformation of NO2 to NO3 is rapid. All phosphorus processes including the algae cycle can be accounted for in both software tools. Both software tools have the ability to simulate both settling and benthic activity, which are important for streams with low velocity. QUAL2E is the only software tool that can simulate temperature using the atmospheric heat balance equation. The third category deals with the additional attributes. QUAL2E provides a built-in uncertainty and sensitivity analysis module, which is useful in determining the sensitivity of input parameters to output water quality. The uncertainty and sensitivity analysis of model parameters is a major component in the overall model development. Based on the above evaluation, WASP5 is considered to be ‘‘over qualified’’ for the development of the Yarra River water quality model. Steady-state simulation is considered sufficient for this study, because it can be used to determine the critical water quality concentrations under design conditions. This is necessary when the model is used to simulate and study the effect of different effluent license limits on river water quality. Furthermore, only grab sample water quality data of the river and at sewage treatment plants are available for the Yarra River. This data limitation can at best be considered as steady state and only suitable to model water quality in one dimension. QUAL2E is also less complex and provides all the essential elements that are required for modeling Yarra River water quality. These elements include modeling of interaction of conventional water quality constituents and the built-in uncertainty and sensitivity analysis. The use of QUAL2E is also supported by a large number of applications in river water quality modeling (15,19).

river water quality models. These water quality models can be used to simulate and assess the cause and effect relationships of river water quality and then to study various management strategies to improve water quality, before their implementation. Many water quality software tools are available in the public domain, which can be used to develop river water quality models. They were reviewed here. After a detailed evaluation of the river water quality modeling tools, QUAL2E was considered as the most suitable tool for use in the Yarra River model development. The major purpose of the development of the Yarra River water quality model is to assess the effect of various sewage treatment plants (STPs) effluent license limits on river water quality and this can be adequately done with QUAL2E software. The major evaluation criteria were the appropriateness of available data for use in the modeling software and the purpose of using the model. BIBLIOGRAPHY 1. Bingner, R., Theurer, F., Cronshey, R., and Darden, R. (2001). AGNPS 2001 Web Site. Available at http://www. sedlab.olemiss.edu/agnps.html. 2. Tim, U., Jolly, R., and Liao, H. (1995). Impact of landscape feature and feature placement on agricultural non-point source pollution control. ASCE J. Water Resour. Plan Manage. 121(6): 463–470. 3. Trauth, K. and Adams, S. (2004). Watershed-based modeling with AGNPS for storm water management. ASCE J. Water Resour. Plan. Manage. 130(3): 206–214. 4. Huber, W.C. and Dickinson, R. (1988). Storm Water Management Model User’s Manual, Version 4, EPA/600/3-88/001a (NTIS PB88-236641/AS). Environmental Protection Agency, Athens, GA. Available at http://ccee.oregonstate.edu/swmm/. 5. U.S. EPA (1997). Compendium of Tools for Watershed Assessment and TMDL Development, Report No. EPA/841/B/97/006. Office of Water, Washington, DC. 6. Bicknell, B., Imhoff, J., Kittle, J., Donigian, A., and Johnson, R. (1997). Hydrological Simulation Program–FORTRAN (HSPF): User’s Manual for Release 11.0, Report No. EPA 600SR97080. National Service Center for Environmental Publication, Cincinnati, OH. Available at http://www.epa.gov/ceampubl/swater/hspf/index.htm. 7. U.S. EPA (1997). Technical Guidance Manual for Developing Total Maximum Daily Loads—Book 2: Streams and Rivers, Report No. EPA/823/B/97/002. Office of Water, Washington, DC. 8. Moore, L., Chew, C., Smith, R., and Sahoo, S. (1992). Modeling of best management practices on North Reelfoot Creek, Tennessee. Water Environ. Res. 64(3): 241–247. 9. Hayashi, S., Murakami, S., Watanabe, M., and Hua, X. (2004). HSPF simulation of runoff and sediment loads in the Upper Changjiang River Basin, China. ASCE J. Environ. Eng. 130(7): 801–815.

CONCLUSION

10. Thomann, R. and Mueller, J. (1987). Principles of Surface Water Quality Modeling and Control. HarperCollins Publishers, New York.

Management of river water quality has become increasingly important due to a decline in water quality caused by human activities. Successful implementation of efficient management strategies requires the development of

11. U.S. EPA (1987). Selection Criteria for Mathematical Models Used in Exposure Assessments, Report No. EPA/600/8/87/042). Office of Health and Environmental Assessment, Washington, DC.

RIVER WATER QUALITY CALIBRATION 12. Brown, L.C. and Barnwell, J.O. (1987). The Enhanced Stream Water Quality Models QUAL2E and QUAL2E UNCAS: Documentation and User Manual, Report No. EPA/600/3-87/OC. U.S. EPA, Athens, GA. Available at http://www.epa.gov/docs/QUAL2E WINDOWS/index.html. 13. Ghosh, N.C. and McBean, E. (1998). Water quality modeling of the Kali River, India. Water, Air Soil Pollut. 102: 91–103. 14. Cvitanic, I. and Kompare, B. (1999). Lessons learned by modelling impounded river water quality with QUAL2E. In: Water Pollution V—Modelling, Measuring and Prediction, WIT Press, Greece. 15. Ning, S., Chang, N., Yang, L., Chen, H., and Hsu, H. (2001). Assessing pollution prevention program by QUAL2E simulation analysis for the Kao-Ping River Basin, Taiwan. J. Environ. Manage. 61, 61–76.

30. 31.

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16. Steynberg, M.C. et al. (1995). Management of microbial water quality: new perspectives for developing areas. Water Sci. Technol. 32(5–6): 183–191.

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17. Barnwell, T., Brown, L., and Whittemore, C. (2004). Importance of field data in stream water quality modeling using QUAL2E-UNCAS. ASCE J. Environ. Eng. 130(6): 643–647.

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18. Shanahan, P., Henze, M., Koncsos, L., Rauch, W., Reichert, P., Somly´ody, L., and Vanrolleghem, P. (1998). River water quality modelling: problems of the art. In: IAWQ 19th Biennial International Conference, 21–26 June 1998, Vancouver, Canada, pp. 253–260.

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19. Mulligan, A.E. and Brown, L.C. (1998). Genetic algorithm for calibrating water quality models. ASCE J. Environ. Eng. 124(3): 202–211.

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20. Ng, A.W.M. (2001). Parameter Optimisation of River Water Quality Models Using Genetic Algorithms [Ph.D. thesis]. Victoria University, Melbourne, Australia.

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21. Grefenstette, J. (1995). A User’s Guide to GENESIS (Version 5.0). Available at http://www. cs.purdue.edu/coast/archive/ clife/Welcome.html. 22. Yang, M., Merry, C., and Sykes, R. (1999). Integration of water quality modeling, remote sensing, and GIS. J. Am. Water Resour. Assoc. 35(2): 253–263.

40.

23. De Azevedo, L. et al. (2000). Integration of water quantity and quality in strategic river basin planning. ASCE J. Water Resour. Plan. Manage. 126(2): 85–97.

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24. Labadie, J. (1994). MODSIM-DSS: generalized river basin decision support system and network flow model. Department of Civil Engineering, Colorado State University. Available at http://modsim.engr.colostate.edu/. 25. Burns, L. (2004). Exposure Analysis Modelling System: User’s Guide For EXAMSII Ver 2.98, Report No. EPA/600/R-00/081. U.S. EPA, Athens, GA. Available at http://www.epa.gov/ ceampubl/swater/exams/exams29804.htm.

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III: Modelling, Measuring and Prediction, Computational Mechanics Publications, UK, pp. 178–188. Lee, J. and Arega, F. (1999). Eutrophication dynamics of Tolo Harbor, Hong Kong. Mar. Pollut. Bull. 39(1–12): 187–192. World Bank. (1997). Pollution Prevention and Abatement Handbook, Part II, Water Quality Models. Available at http://www.esd.worldbank.org/pph/home.html. USACE (1990). CE-QUAL-RIV1: A Dynamic One-Dimensional (Longitudinal) Water Quality Model for Streams, Instruction Report E-90-1. U.S. Army Engineer Waterway Experiment Station, Vicksburg, MI. Available at http://www.wes.army.mil/el/elmodels/index.html#wqmodels. Gore, J.A. and Petts, G.E. (1989). Alternatives in Regulated River Management. CRC Press, Boca Raton, FL. Martin, J. (1988). Application of two-dimensional water quality model. ASCE J. Environ. Eng. 114(2): 317–336. U.S. EPA (2001). Better Assessment Science Integrating point and Nonpoint Sources (BASINS). Available at http://www.epa.gov/waterscience/basins/basinsv3.htm. Ivanov, P., Masliev, I., De Marchi, C., Kularathna, M., and Somly´ody, L. (1996). DESERT User’s Manual: Decision Support System for Evaluating River Basin Strategies. International Institute for Applied System Analysis, Austria. Available at http://www.iiasa.ac.at/Research/WAT/docs/getit.html. Perera, B.J.C. and Somly´ody, L. (1998). Decision support systems for river water quality management. In: Second International Conference on Environmental Management, February 10–13, 1998, Wollongong, Australia, pp. 677–684. Fan, D. (1996). Water Quality Management of the Veszpr´emiS´ed River and Malom and Nador ´ Channel System in Hungry. International Institute for Applied System Analysis, Austria. De Marchi, C., Jolma, A., Masliev, I., Perera, B.J.C., Smith, M.G., and Somly´ody, L. (1996). StreamPlan User’s Manual: Spreadsheet Tool for River Environment Assessment, Management and Planning. International Institute for Applied System Analysis, Austria. Available at http://www.water.hut.fi/wr/research/StreamPlan/. Jolma, A. et al. (1997). StreamPlan: a support system for water—quality management on a river basin scale. Environ. Software Model. 12(4): 275–284. Osmond, D. et al. (1997). WATERSHEDSS: a decision support system for watershed-scale nonpoint source water quality problems. J. Am. Water Resour. Assoc. 33(2): 327–341. NCSU (1994). WATERSHEDSS—a decision support system for nonpoint source pollution control. Available at http://www.water.ncsu.edu/watershedss/.

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26. CEAM (1993). SMPTOX3 Simplified Method Program—Variable Complexity Stream Toxics Model Version 2.01. Available at http://www.epa.gov/ceampubl/swater/smptox3/index.htm. 27. Ambrose, R., Wool, T., and Martin, J. (1988). The Water Quality Analysis Simulation Program, WASP5; Part A: Manual Documentation, Report No. EPA/600/3-87/039. Environmental Research Laboratory, U.S. EPA, Athens, GA. Available at http://www.epa.gov/ceampubl/swater/wasp/index.htm. 28. Lung, W. and Larson, C. (1995). Water quality modeling of Upper Mississippi River and Lake Pepin. ASCE J. Environ. Eng. 121(10): 691–699. ´ ˜ A., Sainz, ´ 29. Suarez, J., Ascorbe, A., Liano, J., Temprano, J., and Tejero, I. (1995). Dynamic simulation of water quality in rivers. WASP5 application to the River Nal´on (Spain). In: Wrobel, L. and Latinopoulos, P. (Eds.), Water Pollution

331

ANNE NG B.J.C. PERERA Swinburne University of Technology Hawthorne, Victoria, Australia

CALIBRATION OF RIVER WATER QUALITY MODELS Introduction River water quality models play an important role in water quality management. Through these models, the cause and effect relationships and the river assimilative capacity can

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be determined so that the appropriate strategies can be implemented in managing river water quality. The process of the model development involves data collection and model selection, model assembly, calibration, validation, and uncertainty and sensitivity analysis. Once the river water quality model is developed using the appropriate river water quality modeling software (refer to REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS in this encyclopedia) and data, it is necessary to calibrate the model before it can be confidently used as a decision-making tool. Model calibration is necessary when the model parameters cannot be measured physically. One such parameter (which cannot be physically measured) is the decay rate of biochemical oxygen demand (BOD), and there are other such parameters in river water quality models. Model calibration is frequently referred to as parameter estimation (1), because the calibration yields the model parameters. Here, methods and techniques used in model calibration (specifically in water related applications) are reviewed first. Then the overall methodology used in calibrating the river water quality model developed for the Yarra River, Australia, using genetic algorithms is presented. Model Calibration Methods Model calibration techniques can broadly be divided into two categories: manual and automatic, as shown in Fig. 1. The manual method is a trial and error method, where the model output due to different parameter sets is compared with observations visually and the parameter set that best matches the model output with observations is selected as the optimum parameter set (2,3). This method is subjective and time consuming. It can also miss the optimum parameter set. It may even lead to unrealistic parameter sets (4,5). The automatic calibration method provides some measure of objectivity to parameter estimation and generally is conducted through optimization. Parameter optimization is achieved in the automatic calibration method through an objective function, which minimizes or maximizes a user-defined function. Several objective functions have been used in the past to assess modeled and observed responses in mathematical models in determining the optimum parameter set. The minimization of the sum

Parameter estimation Manual

Automatic

Trial and error

Optimization Stochastic (Global)

Deterministic (Local)

Direct

Indirect

Random

Guided random

Figure 1. Broad methods in model parameter estimation.

of the squared difference of modeled output (due to different model parameters) and observations residual sum of squares between the actual and modeled values has been commonly used as the objective function in many hydrological studies (5–9). The use of this objective function is known as the least squares method. There are two variations from the least squares method, and they are the simple least squares method (5) and the weighted least squares method (8,9). The difference between these two methods is that the weighted least squares method requires different weights to be attached to each data point in the objective function, whereas in the simple least squares method, the weights are assumed to be equal. As stated by Sorooshian and Gupta (4), the selection of the objective function can be subjective and can produce different results for different objective functions. For example, the optimum model parameters obtained from a catchment model using two different objective functions—one considering peak flows and the other considering runoff volumes—can produce different results. In parameter optimization, an optimization technique is used to determine the optimum parameter set within a prescribed parameter space. As Fig. 1 shows, the optimization techniques can be divided into two broad categories: deterministic and stochastic. The deterministic techniques (also defined as local search methods) determine the optimum parameter set through a systematic search. They are designed to locate the optimum parameter set when the response surface defined by the user-defined function is unimodal (i.e., a single peak/trough). However, if the response surface is multimodal, the parameter set obtained from deterministic methods may not produce the global optimum, since the solution can be trapped at a local optimum point. Starting the optimization with different ‘‘seeds’’ (i.e., starting with different parameter sets for the optimization) may alleviate this problem to a certain extent. Sorooshian and Gupta (4) stated that in calibration of hydrologic models, the optimum parameter set is very rarely found through deterministic methods, since the hydrological problems contain multimodal response surfaces. Duan et al. (10) showed that there were more than hundreds of local optimum solutions in their rainfall and runoff model. Direct and indirect search methods are two deterministic optimization methods. The direct method seeks the optimum by ‘‘hopping’’ around the search space of a predefined grid, where each grid point defines a parameter set, and assessing the objective function at each of these grid points. Basically, these methods use the objective functions of previous two points to determine the next point to be considered in the optimization. Sorooshian and Gupta (4) listed the most common direct search methods used in hydrologic models: Rosenbrock (11), pattern search (12), and Nelder–Mead downhill simplex methods (13). The indirect method (also known as the gradient search method) seeks the optimum solution by defining the next search point, considering both the objective function value and its gradient. Steepest decent, Hessian matrix, and Newton method are examples of indirect methods (4). These three methods have the common feature that they start from a user-defined starting point, but they differ

RIVER WATER QUALITY CALIBRATION

from each other in the direction of moves and the lengths of moves. As compared to deterministic methods, the stochastic methods are more efficient in locating the optimum parameter set, when the response surface is multimodal. However, they can also be used when the response surface is unimodal. Stochastic methods are also known as global search methods, since they are designed to produce the global optimum parameter set. They can be subdivided into two main categories, namely, random and guided random. The random search method generates the parameter sets randomly from the parameter range and optimizes the parameter sets. Generally, the random search method generates a parameter set from a uniform distribution of parameters. It does not consider the history of previous solutions in terms of optimality to determine the next parameter set, and hence the method can be inefficient. On the other hand, the guided random search method provides guided information for the next search based on the history of previously considered points (14). Several guided random search methods exist, such as simulated annealing, adaptive random search, shuffled complex algorithms, and evolutionary algorithms (EAs) (10,14). Of these four methods, EAs have recently been used by many researchers successfully and have attracted wide attention from diverse fields, such as different areas of engineering, computer science, operations research, mathematics, and political science. The growing number of these applications is due to their ease of interfacing, simplicity, and extensibility (15). Evolutionary Algorithms (EAs) Evolutionary algorithms (EAs) are stochastic optimization methods that utilize the natural process of evolution (16). It has been demonstrated that EAs are robust search techniques that outperform the traditional optimization methods in many applications, in particular, when the response surface is discontinuous, noisy, nondifferen¨ tiable, and multimodal (9,17,18). Back and Schwefel (19) stated that EAs have become common and successful techniques in model parameter optimization and have been successfully used in model parameter optimization by Mulligan and Brown (9) and Seibert et al. (20). There are three main forms of EAs: evolutionary programming (21), evolutionary strategies (22), and genetic algorithms (GAs) (17). Apart from these three forms of EAs, there are two other forms that were originally derived from GAs: classifier system (17) and genetic programming (23). These five forms share the common conceptual principle of EAs. That is, they repeatedly apply sequential evolutionary operators that simulate the evolution of parameter sets from the search space. These evolutionary operators are parameter representation, parameter initialization, selection, crossover, and mutation to yield offsprings (or new parameter sets) for the next generation. Depending on the type of EAs, these evolutionary operators are applied simultaneously or selectively. Of these five forms, GAs have proved to provide robust search in complex parameter search spaces. It is also the only form of EAs that utilizes all above five evolutionary operators

333

(i.e., parameter representation, population initialization, selection, crossover, and mutation) (24). Genetic Algorithms (GAs) Genetic algorithms (GAs) are the most prominent and powerful optimization techniques that have been applied successfully recently in many disciplines (25). They are robust search techniques that are based on concepts of natural selection and genetics. For this reason, the terminology used in GAs is borrowed from natural genetics. The reader is referred to Goldberg (17) for details of GAs. The overall GA process as applicable to parameter optimization of river water quality models (or any mathematical model) is described below. Mathematical models have their own model parameters. According to the genetics terminology, each model parameter is a gene, while a complete set of model parameters is a chromosome. The process of a GA begins with an initial population of a number of model parameter sets, which are chosen at random or are heuristic (requires some prior knowledge of the likely ‘‘optimum’’ parameter set) within a specified parameter range. This is the first generation of a number of generations (generally with a constant population size for all generations) in a GA run. Each model parameter set is then evaluated via an objective function to yield its fitness value. The second and subsequent populations (or generations) are generated by combining model parameter sets with high fitness values from the previous population (i.e., parent) through selection, crossover, and mutation operations to produce successively fitter model parameter sets (i.e., offspring). The selection GA operator favors those parent parameter sets with high fitness value over those of lower fitness value in producing offspring. The crossover operator exchanges model parameter values from two selected model parameter sets. The mutation operator adds variability to randomly selected model parameter sets by altering some of the values randomly. Several generations are considered in one GA run, until no further improvement (within a certain tolerance) is achieved in the objective function. The proper selection of GA operators is important for efficient optimization of model parameters. Franchini and Geleati (26) and Ng and Perera (27) investigated the effect of these GA operators on model parameters and found that they were insignificant in achieving the optimum parameter set provided that the widely used GA operators methods and values are used. Wardlaw and Sharif (28), on the other hand, found that different GA operators could produce different optimal solutions. CALIBRATION OF RIVER WATER QUALITY MODEL USING GENETIC ALGORITHMS River Model Development The procedure of calibrating a river water quality model is discussed in this section. The case study discussed is of Yarra River in Australia. No attempt is made to discuss technical results; rather, the overall methodology of calibration using GAs is presented to give readers an

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overview of the calibration procedure. GAs were selected because they have proved to provide a robust search in complex parameter search space. Interested readers can refer to Ng (29) for complete details of the calibration and the results of the case study. The QUAL2E (30) river water quality modeling software tool was selected and used to develop the Yarra River Water Quality Model (YRWQM) (refer to REVIEW OF RIVER WATER QUALITY MODELING SOFTWARE TOOLS in this encyclopedia). A precalibration uncertainty/sensitivity analysis was first undertaken to identify the sensitive and insensitive model parameters. This step was necessary because more effort could then be given to calibration of sensitive parameters during the model calibration. Monte Carlo simulation (MCS) was used for precalibration uncertainty/sensitivity analysis, since it has the ability to consider many different input parameter sets sampled from their distributions and to analyze the output response probability distributions. Interested readers can refer to PARAMETER UNCERTAINTY AND SENSITIVITY ANALYSIS IN RIVER WATER QUALITY MODELS (in this encyclopedia) for a review of different methods used for uncertainty/sensitivity analysis of model parameters. The precalibration uncertainty/sensitivity analysis of YRWQM model parameters and results were discussed in detail in Ng and Perera (31). Linking of YRWQM and GA Software A public domain GA software, namely, GENESIS (32), was used in calibration of YRWQM. GENESIS was selected for this study, since it has been used successfully for different applications (9,33,34) in the past. However, it was necessary to link YRWQM and GENESIS in order to perform the model calibration, since the calibration requires several simulation runs of YRWQM with model parameters generated from GENESIS. Linking was done through input and output files of YRWQM and GENESIS for each calibration event. Procedure in River Water Quality Calibration Several flow events were available for modeling of Yarra River water quality. Each event had information on flow in the river and tributaries, emissions from sewage treatment plants (STPs), and water quality measurements. Three flow events were used in calibration (35), and a further three events were used in validation. Eleven decay rates, which were responsible for nitrogen, phosphorus, and dissolved oxygen, were considered in this calibration (Table 1). This table also shows the influence and relationships of these decay rates on water quality output responses. To use GAs, an appropriate decay rate range is required. These ranges for BODd , NH3 , NO2 , Org-Nd , Org-Pd , BODs , Org-Ns , and Org-Ps reaction rates were derived by applying the standard first-order reaction equation (36) using field data (35). The decay rate range for SOD, NH3 benthos, and Diss-P benthos could not be estimated, because of lack of data. Therefore, the range of decay rates for the three parameters were obtained from Bowie et al. (37), who had compiled results from previous studies. Four water quality output responses, total kjeldahl nitrogen (TKN), total nitrogen (TN), total phosphorus

Table 1. Water Quality Decay Rates Considered in Calibration Decay Rates

Symbols Used in Text

Influence on Output Responses

Org-Nd Org-Ns NH3−d NH3 ben NO2−d Org-Pd Org-Ps Diss-Pben CBODd CBODs SOD

TKN TKN TKN TKN TN TP TP TP DO DO DO

Org-N decay Org-N settling NH3 decay NH3 benthos NO2 decay Org-P decay Org-P settling Diss-P benthos CBOD decay CBOD settling SOD (sediment oxygen demand)

(TP), and dissolved oxygen (DO), were used in calibration and compared with respective observations at six water quality monitoring stations located along the Yarra River. These four output responses require the estimation of eleven water quality decay rates (Table 1). There is some interaction between these output responses (i.e., TKN affects TN, and both TN and TP affect DO) as shown in Fig. 2. The procedure for estimating decay rates was done in a systematic way as shown in Fig. 2 and also stated by McCutheon (38), Wesolowski (39), and U.S. EPA (40). First, the parameters of the water quality constituents that were not affected by other water quality constituents were estimated. Then, these parameters were kept constant, and the parameters of other water quality constituents were estimated as previously. In this study, the objective function based on simple least squares was used, since no information was available on the weights. The simple least squares objective function is given in Equation 1. This equation considers the minimization of squared difference between observed and modeled water quality concentrations at the water quality stations. This squared difference in Equation 1 is known as the fitness in GA. The lower the value, the fitter is the parameter set. Min

 (OBSi − MODi )2

(1)

i=6

where OBSi is the observed water quality concentration at water quality station i, and MODi is the modeled water quality concentration at water quality station i. The first set of parameters considered was Org-Nd , Org-Ns , NH3−d , and NH3 benthos, which are responsible for TKN. Then, these parameters were kept constant as discussed previously and the second parameter set, NO2−d , was optimized considering the output response of TN. The third set of parameters includes Org-Pd , Org-Ps , and DissP benthos and was optimized using the output response of TP. Optimization of decay rates for phosphorus can be done in parallel with TKN and/or TN, since TKN and TN are not influenced by TP and vice versa. The last set of parameters of CBODd , CBODs , and SOD was ‘‘optimized’’ using DO, keeping all other parameters at their optimized values.

RIVER WATER QUALITY CALIBRATION

Org-Nd

Org-Ns

NH3benthos

NH3-d

Org-Pd

Org-Ps

335

Diss-P benthos

TP

TKN Output Response of TKN

Output Response of TP

NO TN2-d TN Output Response of TN

CBODs

CBOD

SOD

DO Output Response of DO

Figure 2. Systematic process used in calibration of YRWQM.

Selection of a Single Optimized Parameter Set Three flow events used in calibration produced three sets of optimum model parameter sets. Selection of a single optimum parameter set from these sets for use in YRWQM requires subjective judgment. An attempt was made to select the single ‘‘optimum’’ parameter set, which models the observed water quality with reasonable accuracy for all three events. The standard student t-test (41) showed the three optimal decay rate sets (obtained from three events) produced equally good water quality predictions that match the observations at 95% significant level. In other words, the use of the three respective optimal decay sets in YRWQM has produced output water quality prediction that does not show any significant difference between modeled and observed water quality. Therefore, another statistical test, known as cumulative absolute relative error (CARE) cited in Reference 40, was used to quantitatively assess which parameter set had produced the overall lowest error with respect to all three events. The CARE value was determined using the following function: Min

 4  6  3   OBSi,j,k − MODi,j,k i=1 j=1 k=1

MODi,j,k

(2)

where OBS is observed water quality, MOD is modeled water quality, i is event used in the calibration (three events), j is output water quality constituents of TKN, TN, TP, and DO (four constituents), and k is water quality sampling stations (six stations). Once the single optimum parameter set was obtained, this set was then used in the validation process.

Validation is a process that assesses the predictability of the model once it has been calibrated. This was done using three independent events, which were not used in the calibration. The model validation will enhance the confidence in using YRWQM for analysis for various management schemes in improving water quality. The student t-test results also showed that the observed and modeled water quality concentrations were not significantly different from each other at 95% significance level for all three validation events. CONCLUSION Simulation models are used to assess various management scenarios in improving river water quality. In order to use these simulation models confidently, the models must be well calibrated. Model calibration (or often referred to as parameter estimation) yields a set of model parameters that best estimate conditions that match with the observations. The calibrated model can then be used to simulate various management scenarios so that the implementation of water quality policy can be done in the most efficient way. Model calibration can be done using manual and automatic methods. The manual methods use trial and error approaches, which are time consuming and require subjective judgment in defining the optimum parameter set. They can often miss the optimum parameter set. The automatic calibration methods provide some measure of objectivity in calibrating the mathematical models and obtaining the optimum model parameters. Genetic algorithms (GAs) are widely used stochastic search

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methods, based on the concepts of natural selection and genetics, which have proved to be successful and efficient in identifying the optimum parameter set in many waterrelated applications. Due to the proven success of GAs as a calibration method, this method was used here to demonstrate the overall methodology in calibrating a river water quality model using the case study of the Yarra River in Australia. The methodology, including model development and linkage with GAs, the process of water quality calibration, and validation, was discussed. BIBLIOGRAPHY 1. Beck, M. (1987). Water quality modeling: a review of the analysis of uncertainty. Water Resour. Res. 23(8): 1393–1442. 2. Tsihrintzis, V., Fuentes, H., and Rodriguez, L. (1995). Calibration and verification of QUAL2E water quality model in sub-tropical canals. In: First International Conference, Aug. 14–18, 1995, Texas, USA, pp. 214–217. 3. Janssen, P. and Heuberger, P. (1999). Calibration of processoriented models. Ecol. Model. 83: 55–66. 4. Sorooshian, V. and Gupta, K. (1995). Model calibration. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology, Water Resources Publications, Littleton, CO, pp. 26–68. 5. Mohan, S. (1997). Parameter estimation of non-linear Muskingum models using genetic algorithm. ASCE J. Hydraul. Eng. 123(2): 137–142. 6. Johnston, P. and Pilgrim, D. (1976). Parameter optimisation for watershed models. Water Resour. Res. 12(3): 477–485. 7. Wang, Q. (1991). The genetic algorithm and its application to calibrating conceptual rainfall-runoff models. Water Resour. Res. 27(9): 2467–2471. 8. Little, K. and Williams, R. (1992). Least squares calibration of QUAL2E. Water Environ. Res. 64(2): 179–185. 9. Mulligan, A.E. and Brown, L.C. (1998). Genetic algorithm for calibrating water quality models. ASCE J. Environ. Eng. 124(3): 202–211. 10. Duan, Q., Sorooshian, S., and Gupta, V. (1992). Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour. Res. 28(4): 1015–1031. 11. Rosenbrock, H. (1960). An automatic method for finding the greatest or least value of a function. Comput. J. 3: 175–184. 12. Hooke, R. and Jeeves, T. (1961). Direct search solutions of numerical and statistical problems. J. Assoc. Comput. Machine 8(2): 212–229. 13. Nelder, J. and Mead, R. (1965). A simplex method for function minimisation. Comput. J. 7: 308–313. 14. Filho, J., Alippi, C., and Treleaven, P. (1994). Genetic algorithm programming environments. IEEE Comput. J. 27(6): 28–63. 15. Dasgupta, D. and Michalewicz, Z. (1997). Evolutionary algorithms—an overview. In: Dasgupta, D. and Michalewicz, Z. (Eds.), Evolutionary Algorithms in Engineering Applications, Springer, New York, pp. 3–28. 16. De Jong, K., Fogel, D., and Schwefel, H. (1997). A history ¨ of computation. In: Back, T., Fogel, D., and Michalewicz, Z. (Eds.), Handbook on Evolutionary Computation (Vol. Part A, Sec. 2.3), Institute of Physics Publishing, Oxford University Press, New York, pp. 1–12. 17. Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimisation and Machine Learning. Addison-Wesley Publishing, Reading, MA.

18. Schwefel, H. (1997). Advantages and disadvantages of evo¨ lutionary computation over other approaches. In: Back, T., Fogel, D., and Michalewicz, Z. (Eds.), Handbook on Evolutionary Computation (Vol. Part A, Sec. 1.3), Institute of Physics Publishing, Oxford University Press, New York, pp. 1–2. ¨ 19. Back, T. and Schwefel, H. (1993). An overview of evolutionary algorithms for parameter optimisation. Evol. Comput. 1(1): 1–23. 20. Seibert, J., Uhlenbrook, S., Leibundgut, C., and Halldin, S. (2000). Multiscale calibration and validation of a conceptual rainfall-runoff Model. Phys. Chem. Earth 25(1): 59–64. 21. Fogel, D.B. (1993). Evolving behaviors in the iterated prisoner’s dilemma. Evol. Comput. 1: 77–97. 22. Schwefel, H. (1981). Numerical Optimisation of Computer Models. John Wiley & Sons, Chichester, UK. 23. Kinnear, J., Smith, R., and Michalewicz, Z. (1997). Derivative ¨ methods. In: Back, T., Fogel, D., and Michalewicz, Z. (Eds.), Handbook on Evolutionary Computation (Vol. Part B, Sec. 1.5), Institute of Physics Publishing, Oxford University Press, New York, pp. 1–15. ¨ 24. Eshelman, L. (1997). Genetic algorithms. In: Back, T., Fogel, D., and Michalewicz, Z. (Eds.), Handbook on Evolutionary Computation (Vol. Part B, Sec. 1.2), Institute of Physics Publishing, Oxford University Press, New York, pp. 1–11. 25. Paz, E. (1998). A survey of parallel genetic algorithms. Available at http://www.illigal.ge.uiuc.edu. 26. Franchini, M. and Galeati, G. (1997). Comparing several genetic algorithm schemes for the calibration of conceptual rainfall-runoff models. Hydrol. Sci. 42(3): 357–379. 27. Ng, A.W.M. and Perera, B.J.C. (2003). Selection of genetic algorithm operators for water quality model calibration. Eng. Appl. Artificial Intell. Elsevier 16(5–6): 529–541. 28. Wardlaw, R. and Sharif, M. (1999). Evaluation of genetic algorithms for optimal reservoir system operation. ASCE J. Water Resour. Plan. Manage. 125(1): 25–33. 29. Ng, A.W.M. (2001). Parameter optimisation of river water quality models using genetic algorithms [Ph.D. thesis]. Victoria University, Melbourne, Australia. 30. Brown, L.C. and Barnwell, J.O. (1987). The Enhanced Stream Water Quality Models QUAL2E and QUAL2E -UNCAS: Documentation and User Manual, Report No. EPA/600/387/OC. U.S. EPA, Athens, GA. 31. Ng, A.W.M. and Perera, B.J.C. (2001). Uncertainty and sensitivity analysis of river water quality model parameters. In: First International Conference on Water Resources Management, Halkidiki, Greece, 24–26 Sep., pp. 175–184. 32. Grefenstette, J. (1995). A User’s Guide to GENESIS (Version 5.0). Available at http://www. cs.purdue.edu/coast/archive/ clife/Welcome.html. 33. Whitley, D. (1989). The genitor algorithm and selection pressure: why rank-based allocation of reproductive trials is best. In: Proceedings of the Third Conference on Genetic Algorithms, June 4–7, 1989, George Mason University, Virginia, pp. 116–121. 34. Liong, S.Y., Chan, W.T., and ShreeRam, J. (1995). Peak-flow forecasting with genetic algorithm and SWMM. ASCE J. Hydraul. Eng. 121(8): 613–617. 35. Ng, A.W.M. and Perera, B.J.C. (2000). Data analysis and preliminary estimates of parameters for river water quality model development. In: Proceedings of the 26th Hydrology and Water Resources Symposium, Perth, Australia, pp. 773–778. 36. Thomann, R. and Mueller, J. (1987). Principles of Surface Water Quality Modeling and Control. HarperCollins Publishers, New York.

SALMONELLA: MONITORING AND DETECTION IN DRINKING WATER 37. Bowie, G., Mills, W., Porcella, D., Campbell, C., Pagenkopf, J., Rupp, G., Johnson, K., Chan, P., Gherini, S., and Chamberlin, C. (1985). Rates, Constants and Kinetic Formulations in Surface Water Quality Modeling, Report No. EPA/600/385/040. U.S. EPA, Athens, GA. 38. McCutcheon, S.C. (1989). Water Quality Modeling, Volume I: Transport and Surface Exchange in Rivers. CRC Press, Boca Raton, FL. 39. Wesolowski, E. (1994). Calibration, Verification, and Use of a Water Quality Model to Simulate Effects of Discharging Treated Wastewater to the Red River of the North at Fargo, North Dakota, Report No. 94-4058. U.S. Geological Survey, North Dakota. 40. U.S. EPA (1997). Technical Guidance Manual for Developing Total Maximum Daily Loads—Book 2: Streams and Rivers, Report No. EPA/823/B/97/002. Office of Water, Washington, DC. 41. Haldar, A. and Mahadevan, S. (2000). Probability, Reliability and Statistical Methods in Engineering Design. John Wiley & Sons, Hoboken, NJ, pp. 97–99.

SALMONELLA: MONITORING AND DETECTION IN DRINKING WATER HEMANT J. PUROHIT ATYA KAPLEY National Environmental Engineering Research Institute, CSIR Nehru Marg, Nagpur, India

INTRODUCTION Providing safe drinking water is one of the challenges faced by most countries due to increasing population and industrialization. The Water Quality Guidelines stated that the most simple waterborne disease risk management involves, among other factors, identifying potential sources of contamination (1). The World Health Organization (WHO) report of March 2001 states that more than three million people die annually from waterborne related diseases. Unsafe drinking water and inadequate sanitation are two of the reasons for this problem. The WHO, conducting a workshop on hazard characterization of pathogens in food and water, launched a program of work with the objective of providing expert advice on risk assessment of microbiological hazards. Salmonella has been identified as one of the key pathogens for risk analysis. Salmonellosis and typhoid fever are the main diseases caused by infection of Salmonella. Salmonellosis is a major public health problem because of its large and varied animal reservoir, the existence of human and animal carrier states, and the lack of a concerted nationwide program to control Salmonella. However, the epidemiology of typhoid fever and other enteric fevers primarily involves person-to-person spread because these organisms lack a significant animal reservoir. Contamination with human feces is the major mode of spread, and the usual vehicle is contaminated water. Typhoid fever is a public health

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problem of which there are an estimated 33 million cases, resulting in 500,000 deaths each year worldwide (2). Different culture media and enrichment methods have been proposed for the isolation of Salmonella species from environmental samples (3,4). Conventional methods for testing Salmonella include the most probable number (MPN) technique (5). Additionally, selective growth media like tetrathionate broth (TB), tetrathionate broth with brilliant-green (TTBG), bismuth sulfide (BS) agar, Salmonella-Shigela (SS) agar, and xylose lysine deoxycholate (XLD) agar are used for enumeration of Salmonella (3). However, these organisms are sometimes difficult to detect or enumerate from the natural ecosystems (6). This is due to Salmonella often entering into the viable and nonculturable state, when exposed to environmental stresses. The routine surveillance of drinking water relies on the growth and biochemical properties of the microorganisms, which is time consuming (3,4). These drawbacks are overcome with the use of molecular tools that can detect even the viable but nonculturable forms with sensitivity and specificity. Molecular tools involve the use of gene probes, enzyme linked assays, and the polymerase chain reaction (PCR). Use of molecular tools for detection of Salmonella has mainly been demonstrated in food samples. There are not many reports that describe detection methods in water samples. Purohit and Kapley (7) have proposed the use of PCR as an option in microbial quality control of drinking water. It is estimated that there are over 40, 000 references to PCR that describe its use in various applications (8). The bottleneck is in getting the PCR as a diagnostic tool from the laboratory to the field, but this needs to be done as a case-specific solution. METHODOLOGY FOR DETECTION USING MOLECULAR TOOLS Sampling and Generation of DNA Methods recommended by the United States Food and Drug Administration require the culture of a sample prior to testing. An aliquot of the overnight grown sample is to be inoculated onto selective media for Salmonella. The suspected colonies are identified by a set of biochemical tests and, if required, further confirmed by conventional serology for Salmonella detection (9). Use of DNA probes and immunodetection systems also require culturing or pre-enrichment of the test sample for a few hours on selective media prior to testing with antibody or DNA probe. Immunofluorescence methods (10) and enzyme immunosorbent assays (11,12) have been successfully used to enrich Salmonella in primary enrichment broths. An electrochemical enzyme-linked immunosorbent assay (ELISA) coupled with flow injection analysis (ELISA-FIA) was used for detecting Salmonella in meat after only 5 h of incubation of pre-enrichment broth (13). Meckes and MacDonald (14) demonstrated the use of a commercially available molecular probe system to isolate and enumerate Salmonella spp. in sludge in less time than cultural techniques with biochemical confirmation. Nucleic acid sequence-based

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amplification (NASBA) results demonstrated the detection of Salmonella in food samples after 18 h of pre-enrichment at initial inoculum levels of 102 and 101 CFU per 25 g food sample. The primer and probe set were based on mRNA sequences of the dnaK gene of Salmonella (15). Direct detection of Salmonella spp. in water samples has also been demonstrated without the use of any pre-enrichment steps using molecular methods (6,16,17). These methods have the advantage of being able to detect Salmonella that are in viable but nonculturable form. Bacteria enter into the nonculturable state on prolonged exposure to river or seawater, due to environmental stresses and limiting nutrient conditions (16,18,19). Such bacteria can still work as etiological agents when they come across the suitable host. Knight et al. (6) demonstrated the use of gene probe for detection from 500–1500 mL seawater samples. Kapley et al. (16) have shown the use of multiplex PCR to detect Salmonella from river water. In this case 5-liter samples were collected and filtered on-site through a 0.2 µm filter. The filter paper with residue was suspended in phosphate buffered saline and brought to the lab on ice within 2 h for analysis. The filter paper with buffer was thoroughly mixed and the cells were harvested from buffer. The total DNA was extracted using proteinase K treatment. The lysed cell preparation was used directly as template for PCR for detection of Salmonella. PCR Based Monitoring The polymerase chain reaction (PCR) is an established molecular technique, which reliably identifies a segment of DNA; and it uses a set of specific subsequences to amplify target segment DNA from a mixed template population. There are some loci reported for amplification target Salmonella along with other members of the Enterobacteriaceae family to detect the main waterborne pathogens but some are highly specific to Salmonella. Way et al. (20) have used multiplex PCR to detect Salmonella and other coliform bacteria. PhoP primers, specific to the phoP/phoQ loci of coliform pathogenic bacteria such as Salmonella, Shigella, Escherichia coli, and Citrobacter species served as presumptive indicators of enteric bacteria. In addition to the phoP primers, the Hin primers, 5′ CTAGTGCAAATTGTGACCGCA 3′ and 5′ CCCCATCGCGCTACTGGTATC 3′ , targeting a 236-bp region of hin/H2 and the H-1i primers, 5′ AGCCTCGGCTACTGGTCTTC 3′ and 5′ CCGCAGCAAGAGTCACCTCA 3′ , amplifying a 173-bp region of the H-1i flagellin gene, were used. Both Hin and H-1i primers are specific to motile Salmonella species and are not present in Shigella, E. coli, or Citrobacter species. Cohen et al. (21) evaluated the suitability of the fimA gene amplification by PCR as a specific method for detection of Salmonella strains. Salmonella typhimurium and other pathogenic members of the Enterobacteriaceae family produce morphologically and antigenically related, thin, aggregative, type 1 fimbriae. Waage et al. (22) demonstrated the detection of low numbers of Salmonella in environmental water by a nested polymerase chain reaction assay. The target loci selected were the conserved sequences within a 2.3 kb randomly cloned DNA fragment from the Salmonella typhimurium

chromosome. The nested PCR assay correctly identified 128 of a total of 129 Salmonella strains belonging to subspecies I, II, IIIb, and IV with a sensitivity of the assay was 2 CFU. No PCR products were obtained from any of the 31 non-Salmonella strains examined. Riyaz-Ul-Hassan et al. (23) also describe a PCR reaction using Salmonella enterotoxin gene (stn) as target loci. The protocol describes the detection of less than 10 cells of Salmonella in 250 mL of blood and approxmately 1 cell in 1 mL of water without any enrichment. Duplex or multiplex reactions further improve over the limitation of the locus-specific detection in PCR or gene probes. A duplex PCR described by Kapley and co-workers demonstrates the use of phoE primers to detect Salmonella in drinking water where Vibrio specific primers were also used in the same reaction (24). Multiplex PCR to detect Salmonella along with different pathogens in a single reaction has also been demonstrated (17,25). While Kapley and co-workers have demonstrated the use of the gene locus that has been shown to be essential for the invasion of Salmonella into epithelial cells of the host’s intestine (inv), Kong and co-workers have used the invasion plasmid antigen B (ipaB) gene of Salmonella typhimurium. The primers for ipaB, forward primer 5′ GGACTTTTTAAAAGCGGCGG 3′ and reverse primer 5′ GCCTCTCCCAGAGCCGTCTGG 3′ , amplified a 314 bp region. A multiplex PCR that amplifies five different loci in a single reaction has been reported for detection of Salmonella from river water samples (16). The gene markers used were invA, SpvA, Spv, and phoE for pathogenic Salmonella, and 16S rRNA specific primers to assess the total eubacterial load in the water samples. The inv locus was chosen as its expression has been shown to be essential for the invasion of Salmonella into epithelial cells of the host’s intestine; causing the gastrointestinal infections (26). The invA gene codes for a protein, which is necessary for virulence of the bacterium. The primers used, upper 5′ -CCTGATCGCACTGAATATCGTACTG 3′ and lower 5′ GACCATCACCAATGGTCAGCAGG 3′ , amplified a 598 bp fragment. The other pathogenic determinants in Salmonella are the plasmid coded virulence Spv genes; SpvA, SpvB, and SpvC (27). More than 80% of all Salmonella isolated from food and clinical specimens contain the virulence factors coded through plasmid (28). The primers reported for spvA upper 5′ TGTATGTTGATACTAAATCC 3′ and lower 5′ CTGTCATGCAGTAACCAG 3′ , amplify a 470 bp product, while the primers reported for spvB, upper 5′ ATGAATATGAAT CAGACCACC 3′ , and lower 5′ GGCGTATAGTCG GCGGTTTTC 3′ amplify a 669 bp product (16). The phoE gene encodes for a phosphate limitation-inducible outer membrane pore protein and has been shown to be Salmonella specific. The primers, upper 5′ AGCGCCGCGGTACGGGCGATAAA 3′ and lower 5′ ATCATCGTCATTAATGCCTAA CGT 3′ , from the phoE locus have already been tested for 133 different Salmonella strains (29). The key to this detection tool has been provided through the thermocycling steps used in the M-PCR. The protocol has used gradient temperature steps, which has provided the selective annealing of primers. The developed multistep program could coamplify the target gene

SALMONELLA: MONITORING AND DETECTION IN DRINKING WATER

markers, used in the study. The specificity of the program has been proved with the DNA template derived from even the river water samples, which represents the heterogeneous microbial population. The most widely used selective primer set for detection of Salmonella has been reported, which are designed from invA locus (30). An extended determination of selectivity by using 364 strains showed that the inclusivity was 99.6% and the exclusivity was 100% for the invA primer set (31). FUTURE OPTIONS IN DETECTION OF SALMONELLA IN WATER SAMPLES With the increasing incidences of spread of waterborne diseases, there is a great need to be able to detect waterborne pathogens like Salmonella (31). The key to this problem is to monitor subtle impacts that may have longterm effects that are hazardous. Genomic tools provide an option for analyzing basic resources at the nucleic acid level of an organism or population of microorganisms. Purohit et al. (32) have reviewed the use of genomic tools in monitoring and assessment processes that can help evaluate the environment impact. These tools can be extrapolated for assessing the mixing of raw sewage waters with water resources. A shortened PCR time with quantification and assured selectivity could be achieved by real time PCR. Based on this concept, an advanced nucleic acid analyzer (ANNA) has been reported that can detect bacteria within 7 min (33). This battery-operated device can be used in the field and has software that can be used by first timers. Inclusion of fluorescent dyes to the DNA during amplification has led to fresh advances in detection methods. Use of molecular beacons, oligonucleotide probes that become fluorescent upon hybridization, have been used in real time PCR assay to detect as few as 2 colony forming units (CFU) per reaction of Salmonella species. This method uses a 122 bp section of the himA as the amplification target. This method could also discriminate between amplicons obtained from similar species such as E. coli and C. freundii. The assay could be carried out entirely in sealed PCR tubes, enabling fast and direct detection of Salmonella in a semiautomated format (34). Detection of 1 colony forming unit/mL in food products was also demonstrated by real time PCR using SipB and SipC as target loci (35). Beyond the real time PCR, protocols need to be developed that can directly detect the pathogen using a biosensor. Kramer and Lim (36) have demonstrated a rapid and automated fiberoptic biosensor assay for the detection of Salmonella in sprout rinse water. Alfalfa seeds contaminated with various concentrations of Salmonella typhimurium were sprouted. The spent irrigation water was assayed 67 h after alfalfa seed germination with the RAPTOR (Research International, Monroe, WA), an automated fiberoptic-based detector. Salmonella typhimurium was identified in spent irrigation water when seeds were contaminated with 50 CFU/g. Viable Salmonella typhimurium cells were also recovered from the waveguides after the assay. This biosensor assay system has the potential to be directly connected to water lines and can assist in process control to identify contaminated water.

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BIBLIOGRAPHY

1. Deere, D., Stevens, M., Davison, A., Helm, G., and Dufour, A. (2001). Management strategies. In: Water Quality—Guidelines, Standards and Health: Assessment of Risk and Risk Management for Water-Related Infectious Disease. World Health Organization, Geneva, Switzerland, World Health Organization, TJ International (Ltd), Padstow, Cornwall, UK. 2. Garmory, H.S., Brown, K.A., and Titball, R.W. (2002). Salmonella vaccines for use in humans: present and future. FEMS Microbiol. Rev. 26: 339–353. 3. Hussong, D, Enkiri, N.K., Burge, W.D. (1984). Modified agar medium for detecting environmental Salmonella by the most-probable number method. Appl. Environ. Microbiol. 48: 1026–1030. 4. Morinigo, M.A., Borrego, J.J., and Romero, P. (1986). Comparative study of different methods for detection and enumeration of Salmonella spp. in natural waters. J. Appl. Bacteriol. 61: 169–176. 5. Russ, C.F. and Yanko, W.A. (1981). Factors affecting salmonellae repopulation in composted sludges. Appl. Environ. Microbiol. 41: 597–602. 6. Knight, I.T., Shults, S., Kaspar, C.W., and Colwell, R.R. (1990). Direct detection of Salmonella spp. in estuaries by using a DNA probe. Appl. Environ. Microbiol. 56: 1059–1066. 7. Purohit, H.J. and Kapley, A. (2002). PCR as an emerging option in the microbial quality control of drinking water. Trends Biotechnol. 20: 325–326. 8. White, T.J. (1996). The future of PCR technology: diversification of technologies and applications. Trends Biotechnol. 14: 478–483. 9. Durango, J., Arrieta, G., and Mattar, S. (2004). Presence of Salmonella as a risk to public health in the Caribbean zone of Colombia. Biomedica 24: 89–96. 10. Thomason, B.M. (1981). Current status of immunofluorescent methodology for salmonellae. J. Food Prot. 44: 381–384. 11. Anderson J.M. and Hartman P.A. (1985). Direct immunoassay for detection of salmonellae in foods and feeds. Appl. Environ. Microbiol. 49: 1124–1127. 12. Mattingly, J.A. and Gehle, W.D. (1984). An improved enzyme immunoassay for the detection of Salmonella. J. Food Sci. 49: 807–809. 13. Croci, L., Delibato, E., Volpe, G., De Medici, D., and Palleschi G. (2004). Comparison of PCR, electrochemical enzyme-linked immunosorbent assays, and the standard culture method for detecting Salmonella in meat products Appl. Environ. Microbiol. 70: 1393–1396. 14. Meckes, M.C. and MacDonald, J.A. (2003). Evaluation of a DNA probe test kit for detection of salmonellae in biosolids. J. Appl. Microbiol. 94: 382–386. 15. D’Souza, D.H. and Jaykus L.-A. (2003). Nucleic acid sequence based amplification for the rapid and sensitive detection of Salmonella enterica from foods. J. Appl. Microbiol. 95: 1343–1350. 16. Kapley, A., Lampel, K., and Purohit, H.J. (2001). Rapid detection of Salmonella in water samples by multiplex PCR. Water Environ. Res. 73: 461–465. 17. Kong, R.Y.C., Lee, S.K.Y., Law, T.W.F., Law, S.H.W., and Wu, R.S.S. (2002). Rapid detection of six types of bacterial pathogens in marine waters by multiplex PCR. Water Res. 36: 2802–2812.

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18. Roszak, D.B., Grimes, D.J., and Colwell, R.R. (1984). Viable but non recoverable stage of Salmonella enteritidis in aquatic systems. Can. J. Microbiol. 30: 334–338. 19. Roszak, D.B. and Colwell, R.R. (1987). Survival strategies of bacteria in the natural environment. Microbiol. Rev. 51: 365–379. 20. Way, J.S. et al. (1993). Specific detection of Salmonella spp. by multiplex polymerase chain reaction. Appl. Environ. Microbiol. 59: 1473–1479. 21. Cohen, H.J., Mechanda, S.M., and Lin, W. (1996). PCR amplification of the fimA gene sequence of Salmonella typhimurium, a specific method for detection of Salmonella spp. Appl. Environ. Microbiol. 62: 4303–4308 (1996). 22. Waage, A.S., Vardund, T., Lund, V., and Kapperud, G. (1999). Detection of low numbers of Salmonella in environmental water, sewage and food samples by a nested polymerase chain reaction assay. J. Appl. Microbiol. 87: 418–428. 23. Riyaz-Ul-Hassan, S., Verma, V., and Qazi, G.N. (2004). Rapid detection of Salmonella by polymerase chain reaction. Mol. Cell Probes 18: 333–339. 24. Kapley, A., Lampel, K., and Purohit, H.J. (2000). Development of Duplex PCR for Salmonella and Vibrio. World J Microbiol. Biotechnol. 16: 457–458. 25. Kapley, A., Lampel, K., and Purohit, H.J. (2000). Thermocycling steps and optimization of multiplex PCR. Biotechnol. Lett. 22: 1913–1918. 26. Clark, C.G., MacDonald, L.A., Ginocchio, C.C., Galan, J.E., and Johnson, R.P. (1996). Salmonella typhimurium invA expression probed with a monoclonal antibody to the Cterminal peptide of InvA. FEMS Microbiol. Lett. 136: 263–268. 27. Suzuki, S. et al. (1994). Virulence region of plasmid pNL2001 of Salmonella enteritidis. Microbiology 140: 1307–1318. 28. Williamson, C.M., Baird, G.D., and Manning, E.J. (1998). A common virulence region on plasmids from eleven serotypes of Salmonella. J. Gen. Microbiol. 134: 975–982. 29. Spierings, G., Elders, R., vanLith, B.M., Hofstra, H., and Tommassen, J. (1992). Characterization of the Salmonella typhimurium phoE gene and development of Salmonella specific DNA probes. Gene 122: 45–52. 30. Rahn, K. et al. (1992). Amplification of an invA gene sequence of Salmonella typhimurium by polymerase chain reaction as a specific method of detection of Salmonella. Mol. Cell Probes 6: 271–279. 31. Malorny, B., Hoorfar, J., Bunge, C., and Helmuth R. (2003). Multicenter validation of the analytical accuracy of Salmonella PCR: towards an international standard. Appl. Environ. Microbiol. 69: 290–296. 32. Purohit, H.J., Raje, D.V., Kapley, A., Padmanabhan, P., and Singh, R.N. (2003). Genomics tools in environmental impact assessment. Environ. Sci. Technol. 37: 356A–363A. 33. Belgrader, P. et al. (1999). PCR detection of bacteria in seven minutes. Science 284: 449–450. 34. Chen, W., Martinez, G., and Mulchandani, A. (2000). Molecular beacons: a real-time polymerase chain reaction Assay for detecting salmonella. Anal. Biochem. 280: 166–172. 35. Ellingson, J.L.E., Anderson, J.L.A., Carlson, S.A., and Sharma, V.K. (2004). Twelve hour real-time PCR technique for the sensitive and specific detection of Salmonella in raw and ready-to-eat meat products. Mol. Cell. Probes 18: 51–57. 36. Kramer, M.F. and Lim D.V. (2004). A rapid and automated fiber optic-based biosensor assay for the detection of Salmonella in spent irrigation water used in the sprouting of sprout seeds. J. Food Prot. 67: 46–52.

LYSIMETER SOIL WATER SAMPLING KEN’ICHIROU KOSUGI Kyoto University Kyoto, Japan

INTRODUCTION The solute concentration of soil water provides important information regarding spatial and temporal distribution of plant nutrients, salinity, and trace elements (1); biological and chemical reactions in soil; and soil and groundwater contamination by industrial wastes and pesticides. For quantifying convective chemical transport in soil, both the water flux and the solute concentration of flowing water should be measured (2). In such a case, a sampling methodology for soil water needs to provide quantitative information on soil water flow as well as to maintain the physical soil environment of the water-sampling profile in a state similar to that of the natural soil profile, as the soil environment affects biological and chemical reactions. TENSION-FREE LYSIMETER One of the traditional techniques for sampling soil water is the tension-free lysimeter, which is also referred to as the zero-tension lysimeter. In this method, a horizontally buried pan intercepts infiltrating water, forming a temporary saturated zone above the pan, and the water drains into a sampling bottle. The tension-free lysimeter collects water only when the soil immediately above the pan has a positive pressure (3). Therefore, the soil in the sampling profile above the lysimeter is wetter than the soil surrounding the lysimeter. With this matric pressure gradient, water will tend to flow from the lysimeter into the surrounding dry-soil region, resulting in an underestimation of the natural water flux (e.g., 4,5). CAPILLARY LYSIMETER In the capillary lysimeter, a wick made of glass or nylon fibers is attached to the base of the water-collecting pan (Fig. 1) in order to establish drier conditions above the lysimeter and to lessen the problem of bypass flow around the lysimeter (6,7). Thus, this device is also referred to as the wick lysimeter. In order to make the water-sampling rate the same as the natural water flux, the length, number, and material of the wicks of the capillary lysimeter must be designed to match the local soil hydraulic properties as well as to respond to the range of fluxes to be encountered (8). However, Gee et al. (3) pointed out that capillary lysimeters tend to undersample when the soil water flux is less than 1000 mm/yr, even if the wick length is optimized for a given soil type. In a laboratory test, Kosugi (9) showed that the capillary lysimeter resulted in wetter conditions in the sampling soil profile than in a natural soil profile, given heavy irrigation of 18.6 mm/h. Recently, Gee et al. (3) proposed extending an impermeable pipe, of about the same diameter as the water-collecting pan, from the base of the pan to a height of

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Sampling tube nonadsorbent material relative to the solutes of interest

Soil surface

Vacuum source Watercollecting pan

Wick

Solution sample container

Soil surface

Sampling tube nonadsorbent material relative to the solutes of interest Figure 1. Schematic diagram of the capillary lysimeter.

15 cm or more, in order to control water divergence around the lysimeter. Although they succeeded in reducing the flux divergence to less than 10% for coarse sand by using a 15-cm-long pipe, they concluded that finer-textured soils might require a pipe that was at least 60 cm long. Such a long pipe might disturb the water-sampling profile and might reduce root water uptake by cutting root systems. Detailed descriptions of the capillary lysimeter are found in Selker (10). TENSION LYSIMETER A generalized version of the capillary lysimeter is the tension lysimeter, which is one of the most frequently used water-sampling techniques. In this method, water is collected through a porous cup or plate by applying suction with a vacuum source instead of a wick. In most cases, porous cup samplers (also referred to as suction cups) are used because of their ease of installation, simplicity of design, and low cost (Fig. 2). However, owing to their small sphere of measurement, the suction cups provide only ‘‘point information,’’ which does not adequately integrate spatial variability (11,12). With the tension lysimeter method, the suction for water extraction is fixed at an empirically decided value between about 20 and 85 kPa (1,13). As a result, the soil moisture condition in the water-sampling profile can be altered depending on the suction applied. In addition, as the volume of soil that is sampled by the tension lysimeter depends on the soil moisture condition at the time of sampling, the soil hydraulic properties, and the flow properties of the lysimeter (12), the water-sampling rate is not necessarily the same as the natural water flux. Moreover, it is reported that the solute concentrations in the sampled water depend on the duration and degree of the sampler vacuum because water extracted from large pores at low suctions may have a different composition from that extracted from micropores at high suctions (14). Corwin (1) provides more information on the tension lysimeter with regard to equipment preparation, installation procedure, and problems.

Porous cup

Figure 2. Schematic diagram of the tension lysimeter.

CONTROLLED-TENSION LYSIMETER In contrast to the above-mentioned techniques, some recent studies have proposed controlling the suction for extracting soil water by referring to matric pressure observations made in the surrounding natural soil profile. The suction control is intended to make the rate of water extraction by the lysimeter the same as the unsaturated water flux in the natural soil profile. Such a ‘‘controlled-tension lysimeter’’ seems to be the most accurate alternative to the methods traditionally used to measure water and convective chemical fluxes in soil. In the controlled-tension lysimeter, the suction is manually or automatically adjusted to a target value determined from tensiometer observations in the natural soil profile (2,15–17), or the suction control is set so that the soil matric pressure immediately above the porous plate should be similar to the matric pressure at the same depth in the natural soil profile (9,18–20). When the two matric pressures are the same, the rate of water extraction by the lysimeter is expected to be similar to the unsaturated water flux in the natural soil profile, because the water-sampling profile has the same upper (i.e., the flux boundary condition defined by rain and irrigation rate) and lower (i.e., the hydraulic head boundary condition) boundary conditions as the natural profile. Thus, the controlled-tension lysimeter method is soundly in accordance with unsaturated flow theory. Figure 3 shows a schematic of a type of controlledtension lysimeter proposed by Kosugi (9) and Kosugi and Katsuyama (20). The equipment consists of two tensiometers (TE) and a ceramic porous plate (PP) connected to a suction system by a sampling tube. The porous plate is buried horizontally in the water-sampling profile. One tensiometer monitors the soil matric pressure immediately above the plate, ψa . The other tensiometer monitors the matric pressure, ψb , at the same depth in a natural soil profile, adjacent to the sampling profile. In the sampling profile, infiltrating water is extracted through the porous plate by applying suction so that ψa = ψb . The suction system consists of a water collection container (WC) connected to a vacuum pump (PU), a valve for releasing the suction (RV), and a pressure transducer (PT) for monitoring the air pressure, pc , in the water collection

342

LYSIMETER SOIL WATER SAMPLING RV

RE AC 100V

RE

PU PT pc

DC

WC

PT ψb

PT ψa

LC

characteristics. Hence, Teflon is not necessarily a suitable material for porous cups and plates (1). Another complicating issue is the change in pH that results from CO2 degassing (23). To reduce CO2 degassing, it is effective to minimize the gas/liquid ratio in the sample container. Collected samples should be tightly capped with the smallest airspace possible remaining in the sample bottle. BIBLIOGRAPHY 1. Corwin, D.L. (2002). Suction cups. In: Methods of Soil Analysis, Part 4—Physical Methods. J.H. Dane and G.C. Topp (Eds.). Soil Science Society of America, Madison, WI, pp. 1261–1266.

Soil surface

Sampling tube TE

TE PP

[Natural profile] DC: Datalogger and controller LC: Load cell PP: Porous plate PT: Pressure transducer PU: Vacuum pump

[Sampling profile] RE: Relay RV: Release valve TE: Tensiometer WC: Water container

Figure 3. Schematic diagram of the controlled-tension lysimeter (modified from Ref. 9).

container. The values of ψa , ψb , and pc are continuously monitored at 3-second intervals. When ψa > ψb (i.e., the sampling profile is wetter than the natural profile), the vacuum pump is turned on in order to extract the water above the porous plate. When ψa < ψb (i.e., the sampling profile is dryer than the natural profile), the pump is turned off and the valve is opened in order to immediately stop water extraction by releasing the suction in the water collection container. During a field test for more than 400 d, the lysimeter maintained the soil moisture condition in the sampling profile similar to that in the natural soil profile and extracted a reasonable amount of water (20). COMMENTS Problems common to the capillary, tension, and controlledtension lysimeters include sample biases caused by contaminations and adsorption as the solution passes through wicks and porous cups or plates. Sample contamination can be significantly reduced by pretreatment of the sampler with an acid wash (1 M HCl solution) and repeated rinsing with a salt solution similar to the soil solution that will be sampled (21). Ceramic, Teflon, and stainless steel are commercially available as materials for porous cups and plates. From among these, ceramic is the greatest in trace metal adsorption (22). Various studies have detailed the adsorption of NH3 , P, and K by ceramic cups. Nonetheless, ceramic is most commonly used for porous cups and plates because it has the lowest cost. Although Teflon is the least reactive, it is hydrophobic and has poor flow

2. Brye, K.R., Norman, J.M., Bundy, L.G., and Gower, S.T. (1999). An equilibrium tension lysimeter for measuring drainage through soil. Soil Sci. Soc. Am. J. 63: 536–543. 3. Gee, G.W., Ward, A.L., Caldwell, T.G., and Ritter, J.C. (2002). A vadose zone water fluxmeter with divergence control. Water Resour. Res. 38: 10.1029/2001WR000816. 4. Jamison, J.M. and Fox, R.H. (1992). Estimation of zerotension pan lysimeter collection efficiency. Soil Sci. 153: 85–94. 5. Chiu, T.F. and Shackelford, C.D. (2000). Laboratory evaluation of sand under-drains. J. Geotech. Geoenviron. Eng. 126: 990–1001. 6. Holder, M. et al. (1991). Capillary-wick unsaturated zone soil pore water sampler. Soil Sci. Soc. Am. J. 55: 1195–1202. 7. Maeda, M., Liyanage, B.C., and Ozaki, Y. (1999). Water collection efficiency of wick samplers under steady state flow conditions. Soil Sci. Plant Nutr. 45: 485–492. 8. Knutson, J.H. and Selker, J.S. (1994). Unsaturated hydraulic conductivities of fiberglass wicks and designing capillary pore-water samplers. Soil Sci. Soc. Am. J. 58: 721–729. 9. Kosugi, K. (2000). A new sampling method of vertical infiltration water in unsaturated soil without disturbing soil moisture condition. J. Jpn. Soc. Hydrol. & Water Resour. 13: 462–471 (in Japanese with English summary). 10. Selker, J.S. (2002). Passive capillary samplers. In: Methods of Soil Analysis, Part 4—Physical Methods. J.H. Dane and G.C. Topp (Eds.). Soil Science Society of America, Madison, WI, pp. 1266–1269. 11. Biggar, J.W. and Nielsen, D.R. (1976). Spatial variability of the leaching characteristics of a field soil. Water Resour. Res. 12: 78–84. 12. Hart, G.L. and Lowery, B. (1997). Axial-radial influence of porous cup soil solution samplers in a sandy soil. Soil Sci. Soc. Am. J. 61: 1765–1773. 13. Tokuchi, N. (1999). Sampling method of solute in soil. In: Methods of Forest Environment Measurement. Hakuyusha, Tokyo, Japan, pp. 186–188 (in Japanese)∗ . 14. Rhoades, J.D. and Oster, J.D. (1986). Solute content. In: Methods of Soil Analysis, Part 1: Physical and Mineralogy Methods. A. Klute (Ed.). Soil Science Society America, Madison, WI, pp. 985–1006. 15. Ozaki, Y. (1999). Bury-type lysimeter to collect infiltrated soil water. In: Proc. Symp., Study on practical problems on monitoring of NO3 -N leaching from crop field. Tsukuba, Japan. Nov. 4–5. National Agriculture Research Center, Tsukuba, Japan, pp. 9–19 (in Japanese)∗ . The title is tentative translation from the original Japanese title by the authors of this paper. ∗

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER 16. Ciglasch, H., Aoungsawad, K., Amelung, W., Pansombat, K., Sombuttun, T., Tarn, C., Totrakool, S., and Kaupenjohann, M. (2002). Fluxes of agrochemicals in an upland soil in Northern Thailand as investigated with novel techniques. Paper 1566. In: Abst., 17th World Congress of Soil Science. Bangkok, Thailand, Aug. 14–21. 17. Lentz, R.D. and Kincaid, D.C. (2003). An automated vacuum extraction control system for soil water percolation samplers. Soil Sci. Soc. Am. J. 67: 100–106. 18. Duke, H.R. and Haise, H.R. (1973). Vacuum extractors to assess deep percolation losses and chemical constituents of soil water. Soil Sci. Soc. Am. Proc. 37: 963–964. 19. van Grinsven, J.J.M. et al. (1988). Automated in situ measurement of unsaturated soil water flux. Soil Sci. Soc. Am. J. 52: 1215–1218. 20. Kosugi, K. and Katsuyama, M. (2004). Controlled-suction period lysimeter for measuring vertical water flux and convective chemical fluxes. Soil Sci. Soc. Am. J. 68: 371–382. 21. Creasey, C.L. and Dreiss, S.J. (1988). Porous cup samplers: cleaning procedures and potential sample bias from trace element contamination. Soil Sci. 145: 93–101. 22. McGuire, P.E., Lowery, B., and Helmke, P.A. (1992). Potential sampling errors: trace metal adsorption on vacuum porous cup samplers. Soil Sci. Soc. Am. J. 56: 74–82. 23. Suarez, D.L. (1986). A soil water extractor that minimizes CO2 degassing and pH errors. Water Resour. Res. 22: 876–880.

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER SUZANNE DU VALL KNORR Ventura County Environmental Health Division Ventura, California

INTRODUCTION Water is essential for the nutrients, metabolic processes, and cellular activity that all living bodies need to survive and thrive. One adult human requires approximately 2.5 liters of potable water from food or liquid sources every day (1). Potable water is water that is fit to drink, free of pathogenic microorganisms or chemicals that are harmful to human health, and free of offensive taste and odors. Drinking water sources include surface waters such as lakes and rivers, and groundwater accessed by wells. Desalination can produce potable water from ocean water, though cost often prohibits widespread use of this method. Public water systems include community, noncommunity, and transient water systems. A water system includes the source water, treatment steps, storage, and the distribution network. Contamination can occur at any point in the water system. Standard treatment methods typically involve several filtration steps to remove larger particles and objects from the source water and sedimentation to allow smaller particles to settle out. Coagulation and flocculation follow sedimentation to remove unsettleable particles. Disinfection to inactivate pathogens commonly involves chlorine, bromine, or ozone, and fine filtration to remove

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protozoa. The treated water may also be pH-stabilized. These treatment methods control most pathogens and inorganic contaminants, such as arsenic and lead, and the secondary drinking water standards of taste, odor, color, and balance. The most common types of industrial chemicals, volatile organic compounds (VOCs), such as benzene (a known carcinogen), toluene, and methyl-tertiary-butyl ether, have been routinely found in groundwater. Removing VOCs requires more extensive treatment methods. Known waterborne disease pathogens can infect healthy adults as well as sensitive populations (young children, pregnant women, elderly adults, and immunocompromised individuals). The Centers for Disease Control (CDC) estimated that over 900,000 incidents of waterborne intestinal disease occur annually, resulting in 900 deaths per year (2). More recently, 39 waterborne disease outbreaks occurred between 1999 and 2000, affecting over 2000 people and resulting in two deaths. Twenty-eight of the 39 were from drinking water that used groundwater sources. Treatment and protection of drinking water sources will not prevent contamination after delivery (point-ofuse). Illness resulting from point-of-use contamination is not considered a waterborne disease incident by the CDC. Household point-of-use treatment methods typically do not remove many organic chemicals (3). Drinking water requirements change as the federal Environmental Protection Agency (EPA) and the CDC further discover the causes of waterborne disease. This article briefly reviews selected contaminants and current regulatory and security requirements that seek to ensure safe and reliable sources of drinking water. SELECTED BIOLOGICAL CONTAMINANTS

Cryptosporidium Cryptosporidium parvum oocysts (cysts) are the infective form of a protozoan smaller than Giardia that is highly resistant to chlorine disinfection and can cause symptoms of acute watery diarrhea (cryptospiridiosis) from as few as 10 cysts. The surface water treatment rule in effect in 1993 did not require the fine filtration needed to remove Cryptosporidium cysts. It is estimated that over 80% of surface water sources are contaminated with Cryptosporidium or Giardia (4). Cryptosporidium can spread in fully chlorinated water, even in the absence of detectable coliforms (5), and medical therapy to treat cryptospiridiosis is limited. The most notable outbreak of waterborne disease caused by Cryptosporidium parvum happened in Milwaukee, Wisconsin, in 1993. This outbreak affected an estimated 403,000 people, resulting in 4400 hospitalizations and 104 deaths (5). It cost city residents an estimated $54 million in medical costs and lost wages (2). Two weeks passed before the waterborne nature of the outbreak was recognized and boil water notices were issued to the public (6). Widespread absenteeism, increased emergency room visits for diarrhea, and a citywide shortage of overthe-counter antidiarrheal medicines led to the detection of the cryptospiridiosis outbreak (5).

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REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER

Investigation of the outbreak revealed that the public water supply came from Lake Michigan and was treated and chlorinated before distribution. Decreased raw source water quality and decreased coagulation and flocculation effectiveness led to increased turbidity in the treated water. The turbidity standards in effect in 1993 allowed daily turbidity measurements in a month not to exceed 1.0 NTU, though periodic spikes above 1.0 NTU were allowed. The highest turbidity measurement was 1.7 NTU, and the treated water had met all state and federal standards at that time (6). The investigation did not find the original source of contamination, but it was determined that the water quality standards ‘‘were not adequate to detect the outbreak’’ (6). This outbreak led to the Interim Enhanced Surface Water Rule in 1998 and later adoption of a primary regulatory standard requiring 99% cyst removal by filtration. Cryptosporidium contaminated water can be disinfected with ozone (4). Point-of-use treatment includes boiling water for 1 minute or filtration with a pore size of 1 micron or smaller (4), which is capable of 99% removal.

(hemolytic uremic syndrome). Unlike other fecal coliforms, E. coli O157:H7 can cause illness from ingesting as few as 10 organisms. One study of a waterborne E. coli O157:H7 outbreak involved 243 patients who used an unchlorinated groundwater supply (32 hospitalizations, 4 deaths) in Burdine township, Missouri, between 12/15/89 and 1/20/90 (7). The case study determined that the largest number of cases of bloody diarrhea was in the municipal water supply service area (7). More recently, four waterborne outbreaks of E. coli O157:H7 occurred between 1999 and 2000, including one in Albany, New York, in 1999. The suspected source in Albany, New York, was contaminated well water consumed at a fair that caused 127 cases of illness, 71 hospitalizations, including at least 10 children with bloody diarrhea; 14 cases of hemolytic uremic syndrome; and two deaths (8,9). The detection of coliforms during routine sampling leads to detecting the presence of fecal coliforms, including E. coli. Standard treatment methods inactivate or remove E. coli O157:H7 or other fecal coliforms. These and other waterborne disease pathogens are included in Table 1.

Escherichia coli O157:H7 Escherichia coli is a fecal coliform, found in the intestines of both humans and animals, that may contaminate water through contact with sewage discharges, leaking septic systems, or water runoff from animal feedlots. Escherichia coli O157:H7 is an enterohemorrhagic strain of one of the four classes of virulent pathogenic E. coli that cause gastroenteritis in humans. It produces a potent verotoxin that damages the intestinal lining, often accompanied by severe bloody diarrhea, particularly in sensitive populations. Severe cases of E. coli O157:H7 can cause renal failure and loss of kidney function

SELECTED CHEMICAL CONTAMINANTS Methyl-tertiary-butyl Ether Methyl-t-butyl ether (MTBE) was introduced in the 1970s as a substitute for lead in gasoline, to reduce emissions and maintain the oxygen level required by the Clean Air Act. MTBE is water-soluble and moves rapidly through soil into groundwater. It is the second most frequently detected chemical in monitoring wells, according to the U.S. Geological Survey (4). Contamination can come from leaking underground fuel

Table 1. Selected Waterborne Pathogens and Parasitesa

Pathogens

Disease

Incubation Period

Estimated Infective Dose, # Organisms

Survival in Water, Days

Up to 50 days 7–21 days 2–8 days

10–50b 10,000–100,000 As few as 10d

Up to 140 days in groundwater Unknownc Up to 20 days in wastewatere

E. coli (all others) Vibrio cholerae Shigella spp.

Type A infectious hepatitis Typhoid fever Hemorrhagic colitis; hemolytic uremic syndrome Enteropathogenic diarrhea Cholera Bacillary dysentery

12–72 hours 1–5 days 1–7 days

108 106 –109 10–100

Cryptosporidium spp.

Cryptosporidiosis

2–21 days

10–100 cysts

Giardia lamblia

Giardiasis

6–22 days

5–100 cysts

Leptospira spp.

4–19 days

Unknown

Entamoeba histolytica

Leptospirosis, hemorrhagic jaundice Amebic dysentery

Up to 45 days in groundwater 5–16 days in surface water 35 days in groundwater; 24 months in surface water Up to 6 months in a moist environment (ova) Up to 4 months in surface water (ova) 3–9 days in surface water

2–4 weeks

10–20 cysts

Ascaris lumbricoides

Ascariasis

2 months

1 cyst, egg or larvae

Hepatitis A virus Salmonella typhi E. coli O157:H7

a

Up to 1 month in surface water (ova) Up to 7 years in soil

Information compiled from Reference 10, unless otherwise indicated. Based on contaminated food consumption (11). c 240 days survival in ice (12). d The infective dose is unknown, but the FDA estimates that the dose may be similar to that of Shigella spp., based on outbreak data and the organism’s ability to transmit person-to-person (13). e Based on information in agricultural research (14). b

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER

tanks, leaking gasoline pipelines, and surface spills. It was detected in groundwater in 55% (3180 out of 5738 sites) of underground leaking gasoline tank sites under investigation in 1998 (15). The oral LD50 for MTBE is approximately 4000 mg/kg, and MTBE was tentatively classified as a possible carcinogen (16). MTBE use has been banned in 11 states. In 2000, the California Senate approved an executive order requesting the ban of MTBE and a proposed phaseout by December 31, 2003 (17). This proposed phase-out has not yet occurred. California has set both primary and secondary standards for MTBE. At the federal level, MTBE is an unregulated contaminant, subject to the Unregulated Contaminant Monitoring Rule (UCMR), and is on the EPA drinking water contaminant candidate list (18). The UCMR requires that all large and selected small public water systems monitor for MTBE. MTBE can be removed in varying amounts through granular activated carbon, air stripping, or advanced oxidation. Perchlorate Perchlorate is an ion with four chlorine attachments, most commonly used in industrial applications. Ammonium perchlorate is used as an energetics booster in explosives, pyrotechnics, rocket fuel, and highway safety flares (19). It has been detected in groundwater in several states, including the Colorado River which supplies water to millions of people (20), and was found most recently in milk and lettuce (21,22). The concern is that perchlorate interferes with iodide uptake by the thyroid gland, leading to a disruption of thyroid hormones that regulate metabolism and growth; continuous thyroid disruptions could cause a hormone imbalance, particularly in pregnant women, developing fetuses, and infants. Several studies show conflicting results, though two studies indicated adverse health effects in susceptible populations at levels as low as 0.01 µg/kg (20,23). Perchlorate can be removed by treatment with ion exchange, ultraviolet light and peroxide, or peroxide and ozone (24). A maximum contaminant level (MCL) has not been established by EPA. The Perchlorate Community Right to Know Act of 2003 mandated an enforceable national perchlorate contaminant standard by July 1, 2004; however, the projected research completion date set by the EPA, necessary for setting a standard, extends beyond this deadline (20,25). The EPA set a reference dose (RfD) of 1 ppb (or 2.1 µg/kg for a 70 kg adult) (26) as part of the draft Health Assessment on Perchlorate in 2002, currently under review by the National Academy of Sciences (NAS) (18). NAS estimates that it will complete the review by December 2004 (13). The RfD is an estimate of the daily dose below which health risks would be considered negligible based on lifetime exposure. The California Department of Health Services (CDHS) was required by law to establish a maximum contaminant level (MCL) for perchlorate by January 1, 2004, although one has not yet been established (27). CDHS set an action level of 6 ppb (28), equivalent to the public health goal (PHG) set by the California Environmental Protection Agency (Cal-EPA) Office of Environmental Health Hazard Assessment (OEHHA). The studies used to establish the

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PHG were criticized by environmental organizations (20). The action level and the PHG are advisory levels, not regulatory requirements. If an action level is exceeded in groundwater, the water system must notify the local governing body (city council or board of supervisors), and CDHS recommends public notification. If an action level is exceeded by ten times, CDHS recommends discontinuing consumption until treated. Eight other states have set advisory levels for perchlorate, ranging from 1 to 18 ppb (29). REGULATORY DRINKING WATER STANDARDS Drinking water must meet the requirements of the Safe Drinking Water Act (SDWA), with monitoring and reporting as specified in the regulation. Individual states may either adopt the federal standard (SDWA) or stricter standards. California adopted stricter standards through the Calderon-Sher Safe Drinking Water Act. Other local drinking water requirements can be found at http://www.epa.gov/safewater/dwinfo.htm. Drinking water sources that include surface waters must be disinfected prior to distribution to the consumer. Current laws and regulations do not require routine treatment of groundwater, unless blended with surface water, although EPA has proposed the Ground Water Rule (GWR) which would require disinfection (8,18). Primary drinking water standards are legally enforceable standards applicable to public drinking water systems, defined as water systems with 15 or more service connections, serving 25 or more people, or operating at least 60 days per year (30). CDHS regulates water systems with five or more service connections. These standards address both biological and chemical contamination and are summarized in Table 2. The maximum contaminant levels (MCL), or specific treatment techniques, such as filtration, used in place of the MCL, as required by the SDWA, are established through evaluation and research to protect public health. Ensuring a safe potable water supply requires vigilance by wholesale and retail water purveyors and water treatment facilities. SDWA requires testing for coliforms, a group of aerobic or facultative anaerobic bacteria commonly found in soil, vegetation, and the intestinal tracts of warm-blooded animals. The presence of coliforms indicates potential fecal coliform contamination and the probability that other pathogens or parasites are also present. Some fecal coliforms survive in water as long as 10 weeks (32). The maximum contaminant level for coliforms is less than or equal to 5% of the water samples that are positive for coliforms when 40 or more samples are collected per month, or one positive sample when less than 40 samples are collected per month (33). The largest public water systems, serving millions of people, must take at least 480 samples per month (34). Smaller systems must take at least five samples per month, unless the state conducted a sanitary survey during the previous 5 years (34). Under certain circumstances, the smallest systems, those serving less than 1000 people, could take one sample per month, not counting repeat sampling (34). Any samples positive for coliforms must also be tested for fecal coliforms. In California, analytical results must be

346

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER Table 2. Current Primary Regulatory Standards for Selected Contaminantsa

Contaminant

EPA, MCL in mg/Lb

CDHS, MCL in mg/Lb

99% removal 99.9% removal 5.0%j 99.99% removal or inactivation 0.010

99% removal 99.9% removal 5.0%j 99.99% removal or inactivation 0.05k

7 MFL 0.05

7 MFL 0.001

0.1 1.3

0.05 1.3

0.2 0.00005

0.2 0.00005

4.0f ,g 0.015 0.002 None 10 1 0.0005

2.0 0.015 0.002 0.013g 10 1 0.0005

0.1

0.1

Nervous system; liver and kidney damage

1.0

0.15

Liver damage; increased risk of cancer

0. 005

0.005

Liver, nervous system, and circulatory system problems Disinfection by-product; liver, kidney, central nervous system effects; increased risk of cancer Kidney toxicity, increased risk of cancer from radionuclides Increased risk of cancer Nervous system damage

0.2

0.2

0.08f

0.10

30 µg/L

20 pCi/L

0.002 10

0.0005 1.750d

Potential Health Effect

Cryptospiridium spp. Giardia lamblia Total coliforms Viruses, enteric

Gastrointestinal illness Gastrointestinal illness Pathogen indicator organism Gastrointestinal illness

Arsenic

Circulatory problems, skin damage, increased risk of cancer Intestinal polyps from ingestion Anemia, reduced blood platelets, increased risk of cancer Variable Gastrointestinal illness, liver and kidney damage Nervous system and thyroid problems Liver, stomach, kidney, and reproductive problems; increased risk of cancer Bone disease; dental discoloration and pitting Developmental effects in children Kidney damage Tentatively classed as possible carcinogen Blue baby syndrome Blue baby syndrome Immune, thymus, reproductive and nervous system damage, increased risk of cancer Liver and kidney damage; circulatory problems

Asbestos Benzene Chromiume Coppera Free cyanide Ethylene dibromide (EDB) Fluoride Leadc Inorganic mercury MTBE Nitrate (as nitrogen) Nitrite(as nitrogen) Polychlorinated biphenyls (PCBs) Styrene (vinyl benzene) Toluene(methyl benzene) Trichloroethylene (TCE)h 1,1,1-Trichloroethane (1,1,1-TCH) Trihalomethanes (TTHMs) Uranium Vinyl chloride Xylenes (total) a

Information from U.S. EPA and California Department of Health Services websites, unless otherwise indicated. MFL = million fibers greater than 10 µm in length per fluid liter; pCi/L = picocuries per liter; 1 pCi = 37 becquerels (Bq) per cubic meter. Food intake is generally measured in Bq/kg or Bq/L. EPA uses 0.9 pCi/µg as a conversion factor (11). c U.S. EPA has a maximum contaminant level goal (MCLG) of 1.3 mg/L for copper and 0.015 mg/L for lead based on the number of samples taken at point-of-use. Additional monitoring, corrosion control, and treatment are required if the regulatory action level is exceeded in more than 10% of samples. Public education is required if the regulatory action level is exceeded for lead. d As a single isomer or the sum of all isomers. e All chromium levels. Hexavalent chromium causes severe diverse health affects, including cancer. It was the groundwater contaminant affecting public health in Hinkley, California, portrayed in the movie ‘‘Erin Brockovich.’’ f EPA standard effective January 1, 2004 for all water systems. g Also has a secondary standard. h TCE was the groundwater contaminant involved in a large leukemia cluster (28 cases in 20 years, four times the national average) in Woburn, Massachusetts, portrayed in the movie, ‘‘A Civil Action’’ (31). j Based on 40 or more samples per month, or one positive sample when less than 40 samples are collected per month. k California must adopt the federal standard, or stricter, by 2006. EPA handles enforcement until the new standard is adopted. b

reported electronically by the tenth day of the following month. The water supplier must retain bacteriological analysis records for at least 5 years, and chemical analysis records for at least 10 years. Wholesale and retail water suppliers are required to provide an annual water quality report (AWQR) to their customers. In California, the Consumer Confidence Report (CCR) acts

as the AWQR, but must adhere to CDHS regulations, which requires contaminant reporting in easy to read table format (35). A violation of a primary drinking water standard requires that the water system take corrective action and notify its customers. The notification must include a description of the violation, what it means using

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER

appropriate health effects language, when it occurred, what action they should take, and who to contact for more information. Violations are classified by tiers under the Public Notification Rule (36,37). A Tier 1 violation requires public notification within 24 hours by radio, television, hand delivery, or other approved means, and concurrent consultation with the appropriate implementing agency (CDHS or EPA where it directly implements the program). Examples of Tier 1 violations are exceeding the MCL for nitrates or nitrites, failure to test for fecal coliforms or E. coli, a repeat fecal coliform positive sample, a waterborne disease outbreak, or other emergency. A Tier 2 violation requires public notification within 30 days. An example of a Tier 2 violation is exceeding the MCL for total coliforms or turbidity. Water system customers must receive notification of a Tier 3 violation within 12 months of the violation. Examples of Tier 3 violations are testing procedure violations or nonfecal coliform monitoring violations. The implementing agency must receive a copy of the public notification within 10 days of initiation for Tier 2 and 3 violations. The water system must send out repeat notifications every 3 months for Tier 2 violations, or every 12 months for Tier 3 violations, for as long as the violation exists. Copies of public notices for Tier 1, 2, and 3 violations must be retained for at least 3 years. The water system must also conduct public notification within 12 months of available monitoring results for unregulated contaminants (36). The implementing agency has formal and informal enforcement actions available to address a failure on the part of the water system to take corrective action or to notify the public or the implementing agency properly. Formal enforcement includes administrative orders, penalties, and civil and criminal actions. States may also refer a recalcitrant water system to the EPA for further enforcement action. Secondary drinking water standards are nonenforceable guidelines for secondary contaminants that may cause cosmetic effects, such as tooth discoloration from high fluoride levels, or aesthetic effects such as a disagreeable taste, odor, or color. Secondary contaminants are defined as any contaminant that adversely affects taste, odor, or appearance, or that may cause a substantial number of people to discontinue use, or that may otherwise adversely affect public welfare. Selected secondary drinking water standards are summarized in Table 3. The water purveyor must notify the public when a secondary drinking water standard is exceeded. Treatment is at the option of the purveyor or the customer at point-of-use. ENHANCED SECURITY REQUIREMENTS The danger of a contaminated water supply to large populations became one focus of the Department of Homeland Security as part of a national directive to protect critical infrastructures. An intentionally introduced biological or chemical contaminant may have a limited effect unless introduced in sufficient quantity. However, the 1993 Milwaukee Cryptosporidium outbreak demonstrated that sometimes a small quantity is all that is necessary to affect a significant portion of the population adversely.

347

Table 3. Current Secondary Drinking Water Standards for Selected Contaminantsa Constituent Color Chloride Fluoride Iron Odor pH Turbidity Sulfates Total dissolved solids MTBE

U.S. EPAb

CDHSb

15 color units 250 mg/L 2.0 mg/L 0.3 mg/L 3 threshold odor units 6.5–8.5 0.5 NTU 250 mg/Ld 500 mg/L

15 color units 250 mg/L Nonec 0.3 mg/L 3 threshold odor units 6.5–8.5 0.5 NTU 250 mg/Ld 500 mg/L

None

0.005 mg/L

a

Information from U.S. EPA and California Department of Health Services websites, unless otherwise indicated. b NTU = nephelometry turbidity units. 0.5 NTU is required for 95% of the daily measurements taken in a monthly period, with no spikes above 1.0 NTU. c Primary standard in California. d 250 mg/L is the lower limit; 500 mg/L is the upper limit.

Two federal laws involving two agencies were passed in 2002: the Homeland Security Act and the Public Health Security and Bioterrorism Preparedness and Response Act (Bioterrorism Act). Both laws pertain to public water systems. The Homeland Security Act requires reporting knowledge of a potential threat to a critical infrastructure, including public water systems, to the Department of Homeland Security. The Bioterrorism Act amended the SDWA to address terrorist and intentional or malevolent acts (threats) against public drinking water supplies. It requires that each public water system serving more than 3300 people conduct a vulnerability assessment (VA), to submit the VA to EPA by deadlines mandated by system size, to prepare an emergency response plan (ERP), and to implement any necessary security enhancements. Interaction between both laws and both agencies must be coordinated within a legal framework. The purpose of the VA is to evaluate the susceptibility of the water system to potential threats and the risk to the community served by the water system and to plan for reducing risks. The VA must include six basic elements (38): 1. characterization of the water system, its mission, and objectives 2. identification and prioritization of adverse consequences to avoid 3. determination of critical assets that may be subject to a threat and potential undesirable consequences 4. assessment of the probability of different types of threats 5. evaluation of existing countermeasures 6. analysis of current identified risks and development of a prioritized plan to reduce these risks The first element involves prioritizing the utility services and the facilities necessary to provide those

348

REGULATORY AND SECURITY REQUIREMENTS FOR POTABLE WATER

services to the community it serves. Characterizing the water system may include a review of operating procedures and management practices for each element within the water system. The systems’ objectives also depend on other utilities, such as power, and the need to evaluate the risk to the system if a threat affects another critical infrastructure. The next two elements involve a review of each component within the water system in relation to any possible threat, including but not limited to physical barriers, water collection, treatment and pretreatment, storage facilities, distribution (including all piping, conveyances, and valves), automated systems, computer systems, and chemical use and storage areas. Preparing these two elements must consider how a threat could affect each element and the potential consequences, such as service disruption, illness, death, or economic impacts. For example, the introduction of a threat contaminant (TC) could involve concentration changes at every stage in the water system as it mixes with clean water or involve reactions with water or piping. Even a weak solution could adversely affect public health, either as an acute exposure to TC dangerous at low doses, or as a chronic health threat to low TC doses over long exposure periods. Each potential disruption in a system’s ability to provide a safe and reliable water supply requires prioritization based on potential magnitude. The fourth element involves identifying different types of threats the system has experienced in the past or that could occur in the future and the probability of each identified possibility. Specific types of threats such as a fire, vandalism, or cyberattacks, might already have specific countermeasures in place. The fifth element involves evaluating the capabilities and limitations of existing risk reduction methods. Examples of these include intrusion detection systems, delay mechanisms (locks, fencing, vehicle access points), and water quality monitoring alarms. The sixth element requires reviewing the vulnerabilities and countermeasures identified in the first five elements and providing recommendations for improvement. VAs were to be completed and sent directly to EPA no later than 3/31/03 for water systems serving 100,000 or more people, no later than 12/31/03 for systems serving 50,000 to 99,000 people, and no later than 6/30/04 for water systems serving less than 50,000 people (39). Compliance with this requirement was voluntary for water systems serving less than 3300 people and updates to the VA are also voluntary (39). The EPA will determine system size based on data in the Safe Drinking Water Information System, submitted by each state in 2002 (30). Some state agencies may require duplicate submission; neither CDHS nor Cal-EPA required a copy of the VA. The EPA plans to review each VA (38). The next requirement of the Bioterrorism Act was for each water system to prepare an Emergency Response Plan (ERP), incorporating the results of the VA. Emergency response planning is essential for the water system to continue to provide a safe and reliable water supply in the event of an emergency. The ERP must include all procedures and equipment that will significantly reduce

the impact of a threat, including basic information such as owner, address, emergency contacts, system components, population served, and number of service connections. The ERP must also identify alternative equipment and water sources, access control, emergency response, and incident specific procedures. Examples of incident specific procedures include policies for handling bomb threats, contamination incidents, or workplace violence. The ERP is to be maintained securely on site. The water system is required to certify to EPA that the ERP was completed within 6 months of VA submission. The water system has the responsibility for ensuring and upgrading security procedures and equipment. CONCLUSION Drinking water laws and regulations were enacted to protect public health. Both the EPA and CDHS also provide information for individuals on private wells so they can protect their water quality. Some waterborne disease outbreaks demonstrate a need to evaluate water quality monitoring methods, and, as in the case of the 1993 Milwaukee cryptospiridiosis outbreak, could lead to a change in regulatory standards. Concerns over the security of critical infrastructures and evaluation of existing systems may also lead to changes that will ultimately enhance protecting public health. As science and technology advances and as more is known about the health affects of waterborne chemical and biological contaminants, drinking water laws and regulations will continue to change. The goal of both the regulatory agencies and the water purveyors should always be to ensure a safe and reliable drinking water supply. BIBLIOGRAPHY 1. Whitney, E. and Boyle, M. (1984). Understanding Nutrition, 3rd Edn. West, pp. 7, 368, 369. 2. Lee, G.F. and Jones-Lee, A. (1993). ‘‘Public Health Significance of Waterborne Pathogens,’’ Report to Cal-EPA Comparative Risk Project, December 1993, http://www.gfredlee.com/ phealthsig 080801.pdf, accessed September 21, 2004. 3. Santa Clara Valley Water District (SCVWD). (2003). Frequently asked questions, perchlorate. May 20, 2003. http://www.valleywater.org/Water/Water Quality/Protect ing your water/ Perchlorate Information/ pdf/Perchlorate FAQ 5-21-03.pdf −436.0 KB, accessed July 28, 2004. 4. Los Angeles Department of Water and Power (LADWP). (2003). MtBE, General Information. http://www.ladwp. com/ladwp/cms/ladwp001420.jsp, accessed July 26, 2004. 5. MacKenzie et al. (1994). A massive outbreak in Milwaukee of Cryptospirodium infection transmitted through public water supply. N. Engl. J. Med. 331(3): 161–167. 6. Centers for Disease Control (CDC). (1996). Surveillance for Waterborne-Disease Outbreaks—U.S., 1993–1994, April 12, 1996. http://www.cdc.gov/epo/mmwr/preview/mmwrhtml/ 00040818.htm, accessed July 23, 2004. 7. Swerdlow et al. (1993). A waterborne outbreak in Missouri of Escherichia coli O157:H7, associated with bloody diarrhea and death. Centers for Disease Control, Enteric Diseases Branch. Annu. Intern. Med. 119(3): 249–250.

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8. Centers for Disease Control (CDC). (2002). Surveillance for Waterborne-Disease Outbreaks—U.S., 1999–2000, Surveillance Summaries. November 22, 2002, http://www.cdc.gov/ epo/mmwr/preview/mmwrhtml/ss5108a1.htm, accessed September 21, 2004.

22. Bustillo, M. (2003). Tests link lettuce to toxin in water. The Mercury News, April 28. http://www.mercurynews.com/mld/ mercurynews/news/5734263.htm, accessed July 28, 2004.

9. New York Department of Health (DOH). (2000). Health commissioner releases E. coli outbreak report. March 31, 2000. http://www.health.ny.us/nysdoh/commish/2000/ecoli.html, accessed September 27, 2004.

23. Silva, A. (2002). Perchlorate goes from obscurity to point of controversy. San Bernardino County Sun, December 14. http://www1800lawinfo.com/practice/printnews.htm?story id =4009, accessed July 28, 2004.

10. Salvato, J.A. (1992). Environmental Engineering and Sanitation, 4th Edn. John Wiley & Sons, Hoboken, NJ.

24. Calgon Carbon Corporation. (2001). Groundwater Remediation Technologies Analysis Center, Case study, Calgon Carbon Corporation—ISEP (R) Continuous Ion Exchange. http://www.perchloratenews.com/case-study1.html, accessed July 28, 2004.

11. Food and Drug Administration (FDA). (2001). Center for Food Safety and Applied Nutrition. Outbreaks associated with fresh and fresh-cut produce, incidence, growth, and survival of pathogens in fresh and fresh-cut produce. September 30, 2001, http://vm.cfsan.fda.gov/∼comm/1 ft3-4a.html, accessed September 20, 2004. 12. Health Canada. (2001). Office of Laboratory Security, ‘‘Material Safety Data Sheet-Infectious Substances, Salmonella typhi. May 15, 2001. http://www.hc-sc.gc.ca/pphb-dgspsp/ msds-ftss/msds134e.html, accessed September 10, 2004. 13. Food and Drug Administration (FDA). (2003). Center for Food Safety & Applied Nutrition, Foodborne Pathogenic Microorganisms and Natural Toxins Handbook, Bad Bug Book, Escherichia coli O157:H7, updated January 7, 2003, http://vm.cfsan.fda.gov/∼mow/chap15.html, accessed September 10, 2004. 14. McCaskey, T.A. et al. (1998). Constructed wetlands controlling E. coli O157:H7 and Salmonella on the farm. Highlights Agric. Res. 45(1): http://www.ag.auburn.edu/aaes/communications/highlights/spring98/ecoli.html, accessed September 20, 2004. 15. Fogg, G.E. et al. (1998). Hydrologic Sciences, Department of Land, Air, and Water Resources, University of California Davis, Impacts of MTBE on California Groundwater. Health and Environmental Assessment of MTBE, Volume 4, Report to the Governor and Legislature of the State of California as Sponsored by SB 521, November 12, 1998. http://www.tsrtp.ucdavis.edu/mtberpt/vol4 1.pdf, accessed September 10, 2004. 16. Office of Environmental Health Hazard Assessment (OEHHA). (1999). California Environmental Protection Agency (Cal-EPA). MTBE in drinking water, California public health goal’’, March 12, 1999, p. 33. http://www.oehha.org/ water/phg/pdf/mtbe f.pdf, accessed September 27, 2004. 17. Office of the Governor. (2002). Governor Davis allows more time for ethanol solution. Press Release PR02:139, March 15, 2002. http://www.energy.ca.gov/releases/2002 releases/200203-15 governor mtbe.html, accessed September 27, 2004. 18. Environmental Protection Agency (EPA). (2002). National Academy of Sciences’ Review of EPA’s Draft Perchlorate Environmental Contamination: Toxicological Review and Risk Characterization. http://cfpub2.epa.gov/ncea/cfm/recordisplay.cfm?deid=72117, accessed September 10, 2004. 19. Calgon Carbon Corporation. (2001). Groundwater Remediation Technologies Analysis Center, About Perchlorate. http://www.perchloratenews.com/about-perchlorate.html, accessed July 28, 2004. 20. Environmental Working Group (EWG). (2004). Rocket fuel in drinking water: Perchlorate pollution spreading nationwide. http://www.ewg.org/reports/rocketwater/, accessed July 28, 2004. 21. Lee, M. (2004). Perchlorate threat looms for farmers. The Sacramento Bee, July 26. http://www.sacbee.com/content/

news/v-print/story/10140109p-11060888c.html, accessed July 26, 2004.

25. Spillman, B. (2003). Boxer’s perchlorate bill doesn’t give EPA enough time. The Desert Sun, March 10. http://www.thedesertsun.com/, accessed July 28, 2004. 26. Food and Drug Administration (FDA). (2004). Center for Food Safety and Applied Nutrition, Office of Plant and Dairy Foods. Perchlorate questions and answers. June 22, 2004. http://www.cfsan.fda.gov/∼dms/clo4qa.html, accessed July 28, 2004. 27. Thompson, D. (2004). State a year tardy in water standards for rocket fuel. Contra Costa Times, January 29, 2004. http://www.contracostatimes.com/mld/cctimes/news/ 7823750.htm, accessed July 28, 2004, SB 1822 Statutes of 2002, available for review at http://www.leginfo.ca.gov. 28. California Department of Health Services (CDHS). (2004). Perchlorate in drinking water: action level July 1, 2004, http://www.dhs.ca.gov/ps/ddwem/chemicals/perchl/ actionlevel.htm, accessed July 28, 2004. 29. Office of Environmental Health Hazard Assessment (OEHHA). (2003). California Environmental Protection Agency (Cal-EPA). Frequently asked questions about the public health goal for perchlorate. http://wwwoehha.org/public info/facts/perchloratefacts.html, accessed July 28, 2004. 30. Environmental Protection Agency (EPA). (2003). Large water systems emergency response plan outline: Guidance to assist community water systems in complying with the public health security and bioterrorism preparedness and response act of 2002. Document EPA 810-F-03-007, July 2003. http://www.epa.gov/safewater/security, accessed September 21, 2004. 31. Durant, J., Chen, J., Hemond, H., and Thilly, W., (1995). Elevated incidence of childhood leukemia in Woburn, Massachusetts. Environ. Health Perspect. Suppl. 103(56): September. 32. Kerr, M. et al. (1999). Survival of Escherichia coli O157:H7 in bottled natural mineral water. J. Appl. Microbiol. 87(6): 833–849. 33. California Health and Safety Code, Section 111145, 111165, 116455 http://www.leginfo.ca.gov/accessed August 4, 2004. 34. Environmental Protection Agency (EPA). (2002). E. Coli O157:H7 in drinking water. http://www.epa.gov/safewater/ ecoli.html, November 26, 2002, accessed September 10, 2004. 35. California Department of Health Services (CDHS). (2004). Consumer Confidence Reports February 13, 2004, http://www. dhs.ca.gov/ps/ddwem/publications/ccr/ccrguideca-02-13-04. pdf, accessed September 28, 2004. 36. California Department of Health Services (CDHS). (2002). Public notification requirements for drinking water regulation violations—proposed regulations. Document R-59-01, pp. 49–52, 58, November 1, 2002.

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37. Environmental Protection Agency (EPA). (2002). Final state implementation guidance for the public notification (PN) rule. http://www.epa.gov/safewater/pws/impguide.pdf, accessed September 28, 2004. 38. Ware, P. (2002). EPA will check drinking water assessments for completeness but will not grade them. December 27, 2002. http://www.amsa-cleanwater.org/advocacy/security/ articles02.cfm, accessed September 10, 2004. 39. Safe Drinking Water Act, 2002, Title IV—Drinking Water Safety and Security, Sections 1433–1435.

READING LIST Environmental Protection Agency (EPA). (2002). MTBE in drinking water. http://www.epa.gov/safewater/mtbe.html, accessed September 14, 2004. Environmental Protection Agency (EPA). (2002). Proposed ground water rule. EPA Document 815-F-00-003, April 2002. http://www.epa.gov/safewater/gwr.html, accessed September 27, 2004. Environmental Protection Agency (EPA). (2002). Radionuclides in drinking water. November 26, 2002. http://www.epa.gov/ safewater/radionuc.html, accessed September 27, 2004. Los Angeles Department of Water and Power (LADWP). (2003). Cryptosporidium, General Information. http://www.ladwp.com/ ladwp/cms/ladwp001423.jsp, accessed July 26, 2004.

A WEIGHT OF EVIDENCE APPROACH TO CHARACTERIZE SEDIMENT QUALITY USING LABORATORY AND FIELD ASSAYS: AN EXAMPLE FOR SPANISH COASTS T.A. DELVALLS ´ M.C. CASADO-MARTINEZ I. RIBA

chemical analysis in sediments to establish contamination, in sediment toxicity to address the biological effects under laboratory conditions, chemical residue analyses in organism tissues to determine the bioavailability of the contaminants, and the structure of the benthic community or the histopathological lesions in resident organisms to determine the biological effects under field conditions (1,2). One of these integrative assessments widely used in the studies of sediment quality is the Sediment Quality Triad that was used synoptically for the first time in Spain and in Europe in the early 1990s (3,4). This method also permits using convenient statistical tools to derive sediment quality guidelines (SQGs), which can be used to derive concentrations associated and not associated with the biological effect in the overlapping area of the different lines of evidences (Fig. 1). Recently, these integrative assessments, and especially the SQT, have suffered some modifications in their interpretation and the representation of their results. In this sense, new methodologies have been incorporated to establish the chronic effects under laboratory conditions, some new parameters were incorporated to avoid the influence of natural casuistry, and especially some new format or representation of the data have been proposed to avoid loss of information, which lacks association with the classic representations (1,6). The main change suffered by the integrative assessment is the change in the names of these methods and they are more precisely known during recent years as weight of evidence approaches (WOE) and defined as concepts instead of as methods. The WOE approach is defined by Burton et al. (7) as ‘‘. . .a process used in environmental assessment to evaluate multiple lines-ofevidence concerning ecological conditions. . . and include

Facultad de Ciencias del Mar y Ambientales ´ Cadiz, Spain ´ -DIAZ ´ M.L. MARTIN J.M. BLASCO

Instituto de Ciencias Marinas de Andaluc´ıa ´ Cadiz, Spain

Contamination Conventionals: OC, grain size, sulfides Metals : Zn, Cu, Pb, Cd, Cr, Hg, Ni, As Organic: ∑7PCBs, PAHTOTAl

Sediment Quality Values

´ N. BUCETA FERNANDEZ

Centro de Estudios de Puertos y Costas Madrid, Spain

THE WEIGHT OF EVIDENCE APPROACH—DEFINITIONS AND LINES OF EVIDENCE During recent years, different initiatives have been carried out to use multiple lines of evidence with the aim to assess sediment quality in aquatic ecosystems. One of the most useful and widely used methods was the design and application of integrative assessments to establish sediment quality (1). These methods comprise the synoptic use of different methodologies such as

In situ Effects Histopathology fish Histopathology clams Bioaccumulation metals: Zn, Cd, Pb, Cu

Toxicity Acute: amphipod survival clam reburial and survival Microtox Chronic: rotifer population decay

Figure 1. Schematic representation of a widely used weight of evidence approach such as the Sediment Quality Triad (SQT). Adapted from Riba et al. (5).

A WEIGHT OF EVIDENCE APPROACH TO CHARACTERIZE SEDIMENT QUALITY USING LABORATORY AND FIELD ASSAYS

assessment of impairment, prioritization of site contamination, and decision-making on management actions.’’ This definition goes farther than the classic definition related to the integrative assessment and the Sediment Quality Triad that were considered methods or concepts instead of processes, including the decisionmaking process. In this sense, we have reviewed here the evolution of the different lines of evidence that have been growing during recent years associated with the use of this kind of WOE approach in Spain from the classic application of the Triad in 1990s and with emphasis on the potential new application for the decision-making processes in the management of sediment quality, including dredged material characterization. Basically, it describes the application of the different lines of evidence in new environmental problems in Spain that have been and are the marine accidental wastes, the management of dredged material, and the assessment of sediment quality in aquatic ecosystems. It describes the use of a conveniently designed battery of sediment toxicity tests to be incorporated in the tier testing approach for the management of the dredged material in Spain, the use of caged animals to help in the relationship between biological effects measured in laboratory and field conditions, the use of bioaccumulation studies either at field or at laboratory conditions to determine the bioavailability of contaminants, and finally, the use of histopathological methods as part of the weight of evidence approach and its use in combination with bioaccumulation of contaminants in different tissues to derive tissue quality values (TQVs) (5,8,9). Finally, some recommendations of the correct process to integrate these results under a weight of evidence approach using the sediment quality triad is proposed for further sediment quality assessment in Spain. DESIGN OF ACUTE SEDIMENT TOXICITY TESTS FOR THE CHARACTERIZATION OF DREDGED MATERIAL IN SPAIN The incorporation of the toxicity test in the management of dredged material disposal is part of a tier testing that is under final development by CEDEX and uses a battery of sediment toxicity tests as a complementary tool to the classic physicochemical analysis using a modification of the sediment quality guidelines (10). This battery of toxicity tests includes the commercial screening test Microtox in the same samples in which chemical analyses are necessary. If doubts about hazardousness of these samples are found in the other two tests, the bioassay using amphipods and the bioassay using sea urchin larvae are conducted classifying the samples as hazardous if any of the tests show positive responses compared with the biological guidelines proposed. THE USE OF CHRONIC, BIOACCUMULATION, AND SUBLETHAL BIOASSAYS TO CHARACTERIZE SEDIMENT QUALITY IN DREDGED MATERIAL One of the recent improvements proposed by different agencies is the possibility to use chronic bioassays having endpoints different from mortality. The main objective

351

is to compare the chronic and acute responses using bioassays to characterize the quality of sediments or dredged material. The toxicity tests involve the comparison of the three proposed acute sediment toxicity tests versus different chronic bioassays using fish (Solea senegalensis) and clams (Scrobicularia plana) and using different sublethal endpoints such as the modification of biomarkers of exposure (methallotioneins, EROD, enzymatic activities of the oxidant stress, etc.) and biomarkers of effect (vitellogenin/vitellin; histopathology). Besides, the complete cycle of an amphipod species (Corophium volutator) is used to address the sediment quality of this material. Results suggest that the biomarkers are a powerful tool to identify the effect in the gray areas in which acute toxicity tests do not show positive responses. In this sense, the use of histopathological studies has permitted the identification of moderate toxicity associated with PCBs that showed absence of effect using the battery of acute toxicity tests (11). The complexities at issue are even greater in the case of evaluating concerns for fish and wildlife at a management site. Assessing the potential for impacts of concern on such receptors requires information about the bioaccumulation potential of contaminants from the sediments or dredged material (e.g., results from a bioaccumulation test), how receptors use the management site, and how specific contaminants will move through the local food web. The proposed chronic tests can be used in the same design as bioaccumulation tests and different chemicals could be analyzed in the same tissues in which biomarker, including histopathological, analysis was performed. These studies will permit one to address the mobility of the different contaminants through the food chain and, specifically in some contaminants, to identify the hazardousness associated with the dredged material, such as in the case of PCBs that can suffer biomagnification processes. The link between the chemical residues and the analysis of biomarker, especially including histopathological diseases in the same tissues by means of bioaccumulationchronic tests, could permit one to derive tissue quality values (TQVs) in a similar approach to those used to derive sediment quality values or guidelines (SQGs) as reported by Riba et al. (5,9). These TQVs could be used to prevent the risk associated with the contaminants in human food of commercial species and contaminants that cannot be identified by the standardized acute toxicity tests. USING in situ APPROACHES TO CHARACTERIZE DREDGED MATERIAL IN SPAIN—CAGING ANIMALS Sediment toxicity tests provide information about toxicity or hazard to sediment-dwelling organisms. However, exposure conditions for benthos at a management site may differ significantly from those occurring in the laboratory. Understanding this difference will require information about the management site, including hydrodynamics (is the site dispersive or depositional?), the area extent of coverage once the material is deposited, how organisms at the disposal site interact with the sediment and overlying

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A WEIGHT OF EVIDENCE APPROACH TO CHARACTERIZE SEDIMENT QUALITY USING LABORATORY AND FIELD ASSAYS

water, and so on. In this sense, different initiatives have been carried out in Spain to address the biological effects under field conditions funded by the Ministry of Science and Technology (DREDGED REN2002 01699/TECNO; TRIADA; VEM2003 −20563/INTER). One of the studies designed to address part of the deficiencies associated with laboratory assays is the use of caged animals at the dredged or disposal site to the measurement of different endpoints, either lethal (12,13) or sublethal (8,13). Some designs of benthic chambers are used with this aim; an example is shown in (Fig. 2). The organisms, basically benthic, are confined in the chamber for ideally the same period of exposure as that used in the bioaccumulation-chronic laboratory assays. The tests need the anchorage of either field-collected or laboratorycultured animals under field conditions exposed to the sediment of concern. The advantages compared with laboratory-exposed devices are that the exposure conditions are representatives of actual conditions at the site. The disadvantages of these field assays are related to the complexities of field-based experimentation, including the difficulties to discriminate the endpoints from noncontaminant variables. In caged experiments, the same parameters as those registered in the laboratory assays are included in the bioassays under field conditions: biomarkers of exposure and effects, chemical concentration in the biological tissues, mortality, and other sublethal endpoints. Another advantage associated with these studies is the potential complementary use with the laboratory tests that permits one to determine the biological effect under field conditions and, by comparing with the laboratory responses, to discriminate some natural causality that is associated with other kinds of approaches to establish biological effect under field conditions, such as the macrobenthic community studies (10).

Figure 2. Schematic representation of the benthic chambers used to expose caged organisms under field conditions. The animals are transported from the laboratory in cold poliespan boxes to the boat. The chambers (50 cm by 25 cm by 15 cm) were immersed and anchored in each sampling station from every port by scuba divers.

FUTURE DEVELOPMENTS The complexity of the matrix defined by sediments or dredged material usually located in highly dynamic ecosystems, such as the littoral areas and especially the estuaries, ensures that successfully using any analytical tool requires having an appreciation for the uncertainties associated with its use. No single test or evaluative tool is able to provide a complete and accurate picture of the complexities inherent in evaluating contaminated sediments. In Table 1, some of the sources of uncertainty associated with applying biological tests to manage dredged material are shown. Notwithstanding the uncertainties included in Table 1, biological tests provide the most direct and certain means for assessing the potential for toxicity and contaminant bioavailability in sediments. Other contaminants exist that are not usually considered in the studies of sediment quality, such as the presence of pathogens in sediments. Microbial pathogens in aquatic systems can contaminate drinking water supplies and/or shellfish and are responsible for hundreds of beach closure events annually. The proximity of sediments to be dredged to sources of pathogens (e.g., sewage outfalls and agricultural runoff) and the presence of conditions favorable for the long-term viability of microbes makes pathogens in sediments or dredged material a matter of growing concern. Unfortunately, standard microbial methods in use worldwide fail to provide adequate information on which to base management decisions. Some pathogens of concern are not associated with the widely used fecal coliform indicator. In addition, some pathogens cannot be cultured from environmental samples using standard media and conditions. Molecular methods are currently being developed to address the deficiencies in current approaches. The molecular approaches under development are not based on the need to culture the pathogens of concern but on extracting and analyzing their DNA. The use of gene-probe technology has the potential to provide a reliable and highly specific method for detecting a pathogen as well as its virulence potential, that is, its ability to cause disease. When such methods are refined and available for widespread use, more credible assessments of pathogens in sediments will be possible. Another point of future research is related to the effects of two key environmental variables, such as pH and salinity in aquatic ecosystems. These two variables control most processes occurring in these environments, and they are especially of interest in the border of aquatic systems, such as those defined by estuaries between marine and freshwater environments. In this kind of ecosystem, these variables, and especially salinity, can play a significant role not only in the partitioning of the contaminants but in the bioavailability and thus in the toxic effects associated with the chemicals. Recently, Riba et al. (14,15) reported the high influence of these variables in the bioavailability of metals from a mining spill that occurred in Spain in April 1998 that affected the Guadalquivir estuary. Their results showed that the same sample tested at different salinity or pH values using a truly estuarine species (Ruditapes phillipinarum) showed significantly higher

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Table 1. Summarized List of Most Common Uncertainties Associated with Biological Testing of Dredged Material. The Uncertainty Description and the Palliative Action to Minimize the Effects on the Final Results Are Included Topic

Uncertainty

Palliative-Minimizing

Extrapolation and number of species in the battery

How the sample is taken and handled prior to testing, and the conditions the sample is subjected to during testing, can affect the accuracy and precision of test results The battery of tests will be composed of a relatively small number of taxa in comparison with the number residing at the site of concern

Dynamism of the ecosystem

Provide only a snapshot of the processes affecting contaminant exposure and effects in sediments

Space scale is limited

The laboratory tests are conducted under controlled conditions of space and may overestimate the extent of exposure and effects given that the movement of the organism are restricted to the material being tested, and water movement (i.e., flow) is minimal Biological tests most commonly measure effects on individual organisms, whereas the ecological impacts of concern occur at the level of populations and communities Test organisms will respond positively and negatively to different experimental variables that are unrelated to the degree of contamination present in a sediment (grain size, food frequency, etc.) Over or underestimate of the hypothesis used in the different tests

Careful and standardized procedures conducted during sediment assessments are necessary to minimize the source of uncertainty in sediment assessment Testing with multiple species that are closely associated with the sediment and have a demonstrated sensitivity to the contaminants of concern Development of more significant tests including chronic tests (at least one cycle of life of the organism) Conduct bioassays under field conditions increasing the space scale in which they are performed to avoid the lack in the extent of exposure and effects associated with the mobility of the organisms

Handling and sampling

Extrapolation to ecological scales

Experimental variables

Results analysis (statistical)

toxicity at salinity values of 10 or lower or at pH values of 6 or lower compared with the toxicity tested at higher salinity or pH values. They relate the effect based on the higher mobility of some metals from sediments to water and also in the speciation of them that changed when the pH and salinity values changed. It informs one of the necessity to incorporate this kind of environmental effect in the final design of the weight of evidence approach, taking into account the potential influence of the pH and salinity values, especially under estuarine conditions. Finally, we recommend to integrative assessment or the more recently cited weight of evidence approaches to avoid or at least minimize most of the deficiencies and uncertainties associated with laboratory and field bioassays. Furthermore, specifically applied WOEs for sediments or dredged material quality assessment is the use of the sediment quality triad incorporating some modifications and improvements to assess the sediment quality in both the disposal and the dredged site. One premise of the method is the design of a tier testing approach based on the definition of the Triad (Fig. 3). In this sense, the incorporation of new chemicals of concern specifically detected in the area to be dredged should be taken into account in the first tiers together with some biological tests for screening of the biological effects. The next steps will lead one to conduct laboratory sediment toxicity and bioaccumulation (if contaminants of concern are present) tests. In this sense, design specific and lowcost chronic tests, including sublethal endpoints such as histopathology, to avoid false negatives of toxicity such as

Selection of the appropriate battery of ecologically relevant organisms

Developing a thorough experimental understanding of the biology and ecology of the test organisms used in biological tests

Ensuring that adequate replication is prescribed to detect a desired magnitude of effect

those associated with specific contaminants. In the last tiers, the use of in situ surveys or those assays under field conditions using caged animals to establish the overall pollution status of the sediment to be dredged are included. The integration of these measurements will permit one to address the environmental quality of the systems and, furthermore, to establish the correct decision-making when selecting the beneficial use and/or the disposal options of the dredged material. These recommended methods are not unique and a more extensive list of potential lines of evidence (7) that can be incorporated into the final tier testing using the weight of evidence approaches, such as the Triad, are included in Table 2. Each of these lines of evidence (LOEs) has their own advantages and limitations, but what is clear is that only one LOE will not be sufficient to address the sediment quality to determine the different management options for dredged material, and the use of several of these LOEs under the final design of a tier testing is recommended using a weight of evidence approach, such as that shown in Fig. 3. Acknowledgments This work has been partially funded by grants funded by the Spanish Ministry of Development (BOE 13-12-02) and of Education and Science (REN2002 01699/TECNO and VEM2003 −20563/INTER). The design of the acute toxicity tests for dredged material characterization was conducted under joint ´ contract between CEDEX and the University of Cadiz (2001 and 2003).

354

A WEIGHT OF EVIDENCE APPROACH TO CHARACTERIZE SEDIMENT QUALITY USING LABORATORY AND FIELD ASSAYS

Table 2. Description of Different Lines of Evidence, Including Their Advantages and Limitations When Used to Assess Sediment Quality and Dredged Material Characterization (7) Line of Evidence

Advantage

Sediment chemistry

Limitation

Relatively simple and standardized. Widely used and utility proved. Cause information Toxicity tests (laboratory) Relatively simple and standardized. Utility proved and widely used. Effect information Tissue chemistry Determination of bioavailability and measure of exposure. If biomagnifications proved: useful in food chain models (human risk) In situ alteration (field Measurements under real environment studies) conditions Biomarkers of exposure Indicators of exposure under either field or (EROD, laboratory conditions, including natural methallotioneins, etc.) variables Biomarkers of effects Indicators of effects under either field or (histology, etc.) laboratory conditions, including natural variables Benthic community Standard methods, in situ conditions. structure Long-term measure of effects, including natural variables Laboratory TIE Partitioning of chemicals under laboratory conditions Field TIE Partitioning of chemicals under field conditions Bethic fluxes of nutrients and/or contaminants Caging animals Tissue quality values (TQVs)

Lack in the effect of information. Assumed feasibility to measure all existing chemicals Lack in the determination of cause. Difficulty in field extrapolation. Natural stressors not assessed Lack in the effect measurements. Difficult to eliminate influence from essential and nonessential chemicals, food chain measurements, acclimation/adaptation No cause is identified. No standard method. Difficult to discriminate natural effects No clear identification of cause, although relative information. Relative relationship to effects. Influenced by natural variables Lack in the cause identification. Nonspecific to contaminants and affected by natural variables Highly affected by natural variables. Not predictive. Confounding factors different from stressors. Absence of organisms in highly disturbed (natural or not) areas Not widely proved. Insensitive. Not available for all chemicals

Highly complex design on the device used. Problems with interpretation of the results. Not possible for all the chemicals. Not standardized Functional capability of the ecosystems High complexity in the devised use. No standard methods. Not widely used for sediment quality but for biogeochemical cycles Toxicity and chemical residues under field Difficult to clearly extrapolate to real conditions. Complex to conditions. Direct exposure to sediments devise and casualty inherent Relationship between sublethal and chemical Not standardized. Relatively new. Large and temporal data residues in organisms tissues base. Not easily available for all chemicals

BIBLIOGRAPHY

Contamination Levels of chemicals in sediments

Sediment Quality Values

In situ Alteration benthic fluxes

3. DelValls, T.A., Forja, J.M., and G´omez-Parra, A. (1998). Environ. Toxicol. Chem. 17: 1073. Toxicity Original nature

Caged animals Histopathological Biomarkers Background: Salinity effects

1. Chapman, P.M. (2000). Int. J. Environ. Pollut. 13: 1. 2. DelValls, T.A., Riba, I., and Mart´ın-D´ıaz, M.L. (2004). Using the triad to characterize dredged material in estuaries: lacks and improvements needed, 4th SedNet Workshop ‘‘Harmonization of Impact Assessment Tools for Sediment and Dredged Materials.’’ June 10–11, San Sebastian, Spain.

Salinity Organisms Truly estuarine

Figure 3. Synoptic representation of the weight of evidence approach recommended in the design of a convenient tier testing method either to assess sediment quality in littoral ecosystems or to manage dredged material. Each circle represents different areas including different lines of evidence (Table 2) to be integrated in the overall integrated approach. The overlapping area permits derivation of sediment quality values and tissue quality values for those overlapping areas, including histopathological and bioaccumulation studies under either field or laboratory conditions.

4. DelValls, T.A. and Chapman, P.M. (1998). Cienc. Mar. 24: 336. 5. Riba, I. et al. (2004). Chemosphere (in press). 6. Riba, I., Forja, J.M., G´omez-Parra, A., and DelValls, T.A. (2004). Environ. Pollut. in press. 7. Burton, G.A. et al. (2002). Hum. Ecol. Risk. Assess. 8: 1675. 8. Mart´ın-D´ıaz, M.L. (2004). Determinaci´on de la calidad ambiental de sistemas litorales y de estuario de la Penı´nsula Ib´erica utilizando ensayos de campo y laboratorio, Tesis ´ Doctoral, Universidad de Cadiz. 9. Riba, I., Blasco, J., Jim´enez-Tenorio, N., and DelValls, T.A. (2004). Chemosphere in press. ´ L.M., Forja, J.M., and G´omez-Parra, 10. DelValls, T.A., Lubian, A. (1998). Environ. Toxicol. Chem. 16: 2323. 11. DelValls, T.A. et al. (2005). Track. Trend. Anal. Chem. (submitted). 12. Riba, I., Casado-Mart´ınez, M.C., Forja, J.M., and DelValls, T.A. (2004). Environ. Toxicol. Chem. 23: 271.

REMEDIATION AND BIOREMEDIATION OF SELENIUM-CONTAMINATED WATERS 13. Mart´ın D´ıaz, M.L., Blasco, J., Sales, D., and Del Valls, T.A. (2003). International Conference on Remediation of Contaminated Sediments. Batelle Press. 14. Mart´ın D´ıaz, M.L., Jim´enez-Tenorio, N., Sales, D., and DelValls, T.A. (2005). Mar. Pollut. Bull. (submitted). 15. Riba, I., Garc´ıa-Luque, E., Blasco, J., and DelValls, T.A. (2003). Chem. Speciation Bioavailab. 15: 101.

REMEDIATION AND BIOREMEDIATION OF SELENIUM-CONTAMINATED WATERS RICHARD M. HIGASHI TERESA A. CASSEL University of California Davis, California

JOSEPH P. SKORUPA U.S. Fish and Wildlife Service

TERESA W.-M. FAN University of Louisville Louisville, Kentucky

GENERAL AND HISTORICAL BACKGROUND The trace element selenium (atomic symbol Se) occurs naturally in soils, water, and biota, including food. It is nutritionally required due to various Se-bearing proteins that incorporate selenocysteine, now recognized as the 21st essential amino acid. In addition to being a required nutrient, Se in excess is toxic to biota (1). The first recorded cases of Se toxicity were penned by Marco Polo during his travels in western China, based on symptoms he observed in livestock (2). In the 1930s, the element Se was attributed to these symptoms, by then known variously as ‘‘alkali disease’’ and ‘‘blind staggers,’’ which afflicted livestock in the western United States (3). However, in certain cases, such symptoms could have been due to other factors (4). For Se, the margin between nutritional requirement and toxicity is unusually narrow and depends on the individual species and circumstance (3). This fact creates a quandary when setting environmentally protective Se criteria. Health benefits of consuming vegetables high in Se are widely touted (5), as cases of human toxicity and crop damage from Se are rare (6). Livestock face both deficiency and toxicity (7), while toxicity is the primary concern with fish, birds, and in particular various aquatic-associated wildlife (8). The latter issue roared to the news headlines as the aquatic bird disaster at California’s Kesterson Reservoir surfaced in the early 1980s (9)—a harbinger of widespread Se problems such as fish mortality and deformities in Belews Lake (10) and numerous other cases internationally (8). A closer look at the affected biota and circumstances surrounding Se toxicity reveals water as the transmitting medium of highest concern (8). Natural water processes (precipitation) and human activities relocate the

355

naturally occurring Se in soils, rocks, and groundwater into collected water bodies that harbor and attract wildlife (8), which might also be used for growing forage and watering livestock (6). Human mobilization of Se mainly consists of irrigation, mine drainage, and surface discharge of groundwater; the latter includes petroleum processing, agriculture, and urban uses. We focus here on the factors important in Se-contaminated water; for the reader interested in the physiology and biochemistry of Se wildlife toxicity, there is an excellent recent review on this complex topic by Spallholz and Hoffman (11). UNDERSTANDING THE PROBLEM: FUNDAMENTALS OF SELENIUM BIOGEOCHEMISTRY In order to solve a problem, it is essential to first understand the nature of the problem. In the case of Se toxicosis of wildlife, exposure to Se primarily occurs through the diet, not by direct exposure to water (12). Therefore, it is vital to understand the ‘‘biogeochemistry’’ of Se: how it moves from contaminated water and sediment to work its way up the foodweb. Figure 1 illustrates the various paths comprising the biogeochemistry of Se. This figure illustrates the first four fundamental facts about wildlife exposure to Se: 1. The paths of Se are numerous and interrelated. 2. Most of the paths eventually lead up the foodweb. 3. Se changes chemical form from an inorganic salt to various organic forms. 4. Some of the organic forms lead to volatilization, a natural path for Se to leave an aquatic system altogether. A fifth important fact, not evident in Fig. 1, is that Se ‘‘bioaccumulates’’ as it heads up the foodweb, generally becoming more concentrated in tissues. This concept may be familiar to many readers, as this phenomenon is discussed widely in the general press and health advisories regarding foodweb bioaccumulation of mercury, pesticides, polychlorinated biphenyls (PCBs), and many other contaminants. Table 1 (13) is an example from the scientific literature that documents this process for Se. Note the very large variation in bioaccumulation factors (BCFs), illustrating the effects of site-specific biogeochemistry in different aquatic systems. A comprehensive study illustrating the complex pathways of bioaccumulation has recently been published (14). SETTING THE REMEDIATION TARGET: THE AQUATIC LIFE CRITERION For remediation to occur, there must first be measurable targets to achieve. The complexity of Se biogeochemistry makes setting such a target extremely difficult to accomplish or even define. An earlier United States Environmental Protection Agency (U.S. EPA) Water Quality Criterion for Se, which set a maximum of 5 µg/L total Se, provided a clear target (15).

356

REMEDIATION AND BIOREMEDIATION OF SELENIUM-CONTAMINATED WATERS

Figure 1. Biogeochemical cycling of Se in aquatic ecosystem. This scheme is modified from Reference 13. Arrows indicate processes that can lead to risk from foodweb accumulation of Se (‘‘ecotoxic’’ risk). Other arrows trace the Se volatilization process by which Se can be lost from the aquatic system. a, Uptake and transformation of Se oxyanions by aquatic primary and secondary producers; much of the biotransformation pathway is yet to be defined. b, Release of selenonium and other organic Se metabolites by aquatic producers. c, Uptake of organic Se compounds by aquatic producers. d, Abiotic oxidation of organic Se compounds to Se oxyanions. e, Release of alkylselenides from selenonium or other alkylated Se precursors through abiotic reaction. f, Release of alkylselenides from selenonium or other alkylated Se precursors through aquatic producers. g, Volatilization of alkyselenides into the atmosphere. h, Oxidation of alkylselenides to Se oxyanions. i, Formation of red amorphous Se element by aquatic and sediment producers. j, Detrital formation from aquatic producers. k, Se bioaccumulation into the foodchain with potential ecotoxic consequences; the toxic form(s) are yet to be defined. l, Assimilation of waterborne selenium oxyanions into sediment biota. m, Oxidation of sediment Se(0) to oxyanions. n, Reduction of sediment Se(0) to Se(−II) or vice versa. o, Assimilation of sediment Se(−II) into sediment biota. p, Oxidation of sediment Se(−II) to selenite.

Gaseous selenides

g Drainage

Organic volatile selenides

Selenite

Selenate

SeO32−

SeO42−

h e

d CH3 + CH3 Se + Οther Se forms (−2→0) R

f

Ecotoxic risk

c a

b

SeO42−

I

Organic Se

SeO32−

a′

Aquatic producers, e.g. algae, bacteria, plants

m′ i

Aquatic consumers

I′

m p

Se

n Se(−II)

The setting of this temporary value spawned numerous attempts to apply the three traditional strategies of remediation, which are containment, removal, and treatment (16). However, such a criterion for remediation remains very much a ‘‘moving target’’ due to the complexity of the biogeochemistry. In particular, there are currently attempts to develop a more scientifically sound U.S. EPA Aquatic Life Criterion for Se (17), for which there is now a draft (18). What follows is a very abbreviated description of the issues surrounding the setting of an Aquatic Life Criterion. For a more complete understanding, the reader should refer to the cited literature. Several independent studies submitted to the U.S. EPA estimated that the 5-µg/L Se toxicity threshold was either too high or too low; interestingly, arguments for higher or lower thresholds appear to be closely associated with whether researchers were affiliated with the corporateservice (arguing that 5 µg/L is too low) or public-service (arguing that 5 µg/L is too high) scientific communities. A slightly different formulation of this observation has also been presented elsewhere (19). Additionally, the proposed California Toxics Rule of 5 µg/L Se in water (20)

0

Detritus

k i′

k

J k

Sediment organisms, e.g. microbes, insect larvae

k

O

was judged by the U.S. Fish and Wildlife Service to be too high (21), jeopardizing 15 species protected by the Endangered Species Act (22), the majority of which were aquatic-dependent wildlife that do not actually live in the water. The lesson here is that, because of the biogeochemistry of Se, it is important to include consideration of the entire aquatic-based foodweb, not just aquatic organisms. Recently, the U.S. EPA contracted the Great Lakes Environmental Center to derive chronic Se criteria on a fish-tissue basis, rather than the traditional water concentration basis. The results of this analysis were considered to have limited applicability because it produced a threshold (7.9 µg Se/g tissue) based on an LC20 (lethal concentration at which 20% mortality is expected), which is not adequately protective of the species of concern (22). Several other flaws were found in the study, which essentially compiled experimental data from 17 published studies (18). One of these (23) is qualitatively distinct because it incorporated a ‘‘winterstress’’ design accounting for the increase in toxicity of dietary Se to birds, fish, and mammals under low temperatures. Adjustment of these data for the

REMEDIATION AND BIOREMEDIATION OF SELENIUM-CONTAMINATED WATERS

357

Table 1. Excerpted Data from Reference 13 Illustrating Bioaccumulation of Se and the Great Variance in the Bioconcentration Factors of Se Salinity, ppth

Waterborne Se, µg/L

Body Burden, µg/g

BCF

Algae Algae Algae Algae Algae Algae Algae Algae Algae Average S.D.

76 14 41 136 80 10 47 66 54 58.2 38.1

13.5 7.9 7.0 13.1 13.3 6.0 5.2 5.1 8.7 8.8 3.5

11.8 14.8 16.0 9.7 22.6 1.5 11.7 9.9 8.6 11.8 5.8

873 1877 2281 745 1695 247 2273 1954 978 1436 738

Midge larvae Benthic composite Water column composite Corixid Corixid Artemia + corixid Artemia Corixid Artemia Artemia Artemia Midge larvae Artemia Average S.D.

12 76 76 39 90 126 108 108 47 66 54 8.3 67 67.5 35.8

5.2 5.8 5.8 7.5 8.8 11.5 12.2 12.2 5.6 4.9 9.5 2.5 506.0 46.0 138.3

18.1 7.4 12.3 8.9 6.8 11.7 9.0 10.1 9.8 16.6 10.9 42.3 19.6 14.1 9.4

3489 1288 2130 1187 778 1012 740 834 1749 3372 1145 16886 39 2665 4389

chronic-level protection needed (90%.

Higher Death trophic levels Sustained harvesting D

Death

B Plants, algae, & microbes

A

SeO3 SeO4

Uptake by sediment-ingesting organisms E

Se in humic material

C Volatile Se compounds as by-products

Se in detrital material

Invertebrates

Fixation of Se

is consideration given that the aquatic system may be mostly functioning ‘‘right,’’ and only a few particular processes that are awry need to be addressed. ‘‘Biovolatilization’’ of Se is one such approach, since it takes advantage of the natural biogeochemistry to remove Se. The problem with biovolatilization of any type, as Fig. 1 outlines, is that the process also draws Se into the biota, and consequently up the foodweb. This tendency has been particularly troublesome in attempts to utilize aquatic vascular plants to volatilize Se. For example, vascular plants volatilize a relatively small amount of Se while sequestering it in bioavailable foodweb materials such as the shoots and roots. Although the shoots could be harvested and disposed, the Se is mostly contained in the below-ground portions of the plants (31), which are not practical for harvesting. Fan and Higashi (28,32) have described natural algal Se volatilization as part of an alternative remediation process in terminal basins. The overall remediation process, outlined in Fig. 2, combines volatilization of Se with interrupting the foodweb accumulation of Se (33). In this strategy, photosynthetic algae function to volatilize Se while serving as food to macroinvertebrates (brine shrimp). The brine shrimp graze the algae, ideally preventing algal accumulation and participation in the detrital cycle. In turn, the brine shrimp are harvested as a marketable product, thereby intercepting the foodwebaccumulated Se before it can impact fish and birds. Both volatilization and harvesting of brine shrimp result in a net removal of Se from the aquatic system. The resulting blockages to the foodweb accumulation of Se are shown by the X’s in Fig. 2. A full-scale evaporation basin system has been monitored for over three years in this regard (33). The terminal evaporation basins are brine, which allows the flourishing of brine shrimp that has commercial value—in fact, at California’s Tulare Lake Drainage District, there has been successful commercial harvesting of brine shrimp for over five years (34). The efficacy of the approach is clear: (1) the algae that volatilize Se and feed the brine shrimp grow naturally in these basins; (2) the brine shrimp also grow naturally in these basins to a high density; (3) much of the scheme utilizes water management that is familiar to drainage operators; and (4) costs of encouraging and managing brine shrimp growth is offset by marketing harvested materials. Comparisons with analogous systems where brine shrimp harvesting is not implemented has demonstrated that, under active brine shrimp harvesting (33):

359

Availability to sediment microorganisms? Organic matter

Figure 2. Bioremediation in drainage basins by reducing Se ecotoxic risk through invertebrate harvest and Se volatilization. In this ‘‘biogeochemical reflux’’ scheme, the drainage inorganic Se forms are initially biologically fixed by aquatic algae and A . The fixed Se does not directly head up the microbes foodchain in the water column, as is often portrayed. Instead, a major fraction enters into organic matter, taking a detour through detritus (recently dead organic matter) and sediment B , then reentering the foodchain at several trophic levels

C . Over longer periods, part of the detrital material is

D , locking up the converted to recalcitrant humic material Se until sediment-ingesting organisms reintroduce them to the E . Through sustained harvesting (upper left box) foodchain of water-column invertebrates that consume algae and microbes, the bioavailable Se is removed from water, plus detrital formation resulting from the death of water-column organisms is also blocked. Both types of blockages are shown by the three X’s. In turn, this would help minimize the sediment–detritus foodchain pathway for Se. In the meanwhile, additional Se can be removed by manipulating the algae/microbe community for optimal Se volatilization (lower left box).

Research is continuing to determine how this strategy can be applied to other systems and to achieve longterm sustainability. At present, the combined strategy of impounding Se-contaminated water in basins, applying the algal volatilization–foodweb interruption process, and constructing compensation/alternative habitats illustrates the advantages of an integrated management approach. In fact, such watershed-scale management appears to be required in order to remediate a contaminant with complex biogeochemistry such as Se. BIBLIOGRAPHY 1. Cooper, W.C. and Glover, J.R. (1974). The toxicity of selenium and its compounds. In: Selenium. R. Zingaro and W.C. Cooper (Eds.). Van Nostrand Reinhold, New York.

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SHELLFISH GROWING WATER CLASSIFICATION

2. Marsden, X. (1962). The Travels of Marco Polo (1271–1285). The Heritage Press, Norwich, CT. 3. Combs, G.F. Jr., Levander, O.A., Spallholz, J.E., and Oldfield, J.E. (Eds.). (1987). Selenium in Biology and Medicine. Van Nostrand Reinhold, New York. 4. O’Toole, D. and Raisbeck, M.F. (1998). Magic numbers, elusive lesions: comparative pathology and toxicology of Selenosis in waterfowl and mammalian species. In: Environmental Chemistry of Selenium. W.T. Frankenberger and R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 355–395. 5. Keck, A.-S. and Finley, J.W. (2004). Cruciferous vegetables: cancer protective mechanisms of glucosinolate hydrolysis products and selenium. Integrative Cancer Therapies 3(1): 5–12. 6. Engberg, R.A., Westcot, D.W., Delamore, M., and Holz, D.D. (1998). Federal and state perspectives on regulation and remediation of irrigation-induced selenium problems. In: Environmental Chemistry of Selenium. W.T. Frankenberger, R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 1–25. 7. Maas, J. (1998). Selenium metabolism in grazing ruminants: deficiency, supplementation, and environmental implications. In: Environmental Chemistry of Selenium. W.T. Frankenberger and R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 113–128. 8. Skorupa, J.P. (1998). Selenium poisoning of fish and wildlife in nature: lessons from twelve real-world examples. In: Environmental Chemistry of Selenium. W.T. Frankenberger and R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 315–354. 9. Ohlendorf, H.M. (2002). The birds of Kesterson Reservoir: a historical perspective. Aquat. Toxicol. 57: 1–10. 10. Lemly, A.D. (2002). Symptoms and implications of selenium toxicity in fish: the Belews Lake case example. Aquat. Toxicol. 57: 39–49. 11. Spallholz, J.E. and Hoffman, D.J. (2002). Selenium toxicity: cause and effects in aquatic birds. Aquat. Toxicol. 57: 27–37. 12. Presser, T.S. and Ohlendorf, H.M. (1987). Biogeochemical cycling of selenium in the San Joaquin Valley, California, USA. Environ. Manage. 11: 805–821. 13. Fan, T.W.-M., Teh, S.J., Hinton, D.E., and Higashi, R.M. (2002). Selenium biotransformations into proteinaceous forms by foodweb organisms of selenium-laden drainage waters in California. Aquat. Toxicol. 57: 65–84. 14. Stewart, A.R., Luoma, S.N., Schlekat, C.E., Doblin, M.A., and Hieb, K.A. (2004). Food web pathway determines how selenium affects aquatic ecosystems: a San Francisco Bay case study. Environ. Sci. Technol. 38: 4519–4526. 15. U.S. Environmental Protection Agency (1987). Ambient Water Quality Criteria for Selenium. EPA, Washington, DC, EPA440/5-87/083. 16. Brusseau, M.L. and Miller, R.M. (1996). Remediation. In: Pollution Science. I.L. Pepper, C.P. Gerba, and M.L. Brusseau (Eds.). Academic Press, San Diego, Chap. 11, p. 154. 17. Sappington, K.G. (2002). Development of aquatic life criteria for selenium: a regulatory perspective on critical issue and research needs. Aquat. Toxicol. 57: 101–113. 18. Aquatic Life Water Quality Criteria for Selenium (2002). Draft Document Prepared for the United States Environmental Protection Agency, Washington, DC, by the Great Lakes Environmental Center, Traverse City, MI, p. 67. 19. Hamilton, S.J. (2004). Review of selenium toxicity in the aquatic food chain. Sci. Total Environ. 326: 1–31. 20. EPA (1997). Water quality standards; establishment of numeric criteria for priority toxic pollutants for the State of California. Fed. Reg. 62(150): 42159–42208.

21. Final Biological Opinion on the Effects of the U.S. Environmental Protection Agency’s ‘‘Final Rule for the Promulgation of Water Quality Standards: Establishment of Numeric Criteria for Priority Toxic Pollutants for the State of California’’ (2000). United States Department of Interior: Fish and Wildlife Service and United States Department of Commerce: National Marine Fisheries Service, p. 323 22. United States Code [U.S.C.] (2000). The Endangered Species Act of 1973. 16 U.S.C., Sections 1531–1544. 23. Lemly, A.D. (1993). Metabolic stress during winter increases the toxicity of selenium to fish. Aquat. Toxicol. 27: 133–158. 24. Ohlendorf, H.M. (2003). Ecotoxicology of selenium. In: Handbook of Ecotoxicology, 2nd Edn. D.J. Hoffman, B.A. Rattner, G.A. Burton Jr., and J. Cairns Jr. (Eds.). Lewis Publishers, Boca Raton, FL, pp. 465–500. 25. The TMDL regulations and literature are very extensive—for more information, access the website http://www.epa.gov/ owow/tmdl/. 26. Tanji, K. et al. (2003). Evaporation ponds as a drainwater disposal management option. Irrigation Drainage Syst. 16: 279–295. 27. Frankenberger, W.T. and Engberg, R.A. (Eds.). (1998). Environmental Chemistry of Selenium. Marcel Dekker, New York. 28. Fan, T.W.-M. and Higashi, R.M. (1998). Biochemical fate of selenium in microphytes: natural bioremediation by volatilization and sedimentation in aquatic environments. In: Environmental Chemistry of Selenium. W.T. Frankenberger and R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 545–563. 29. Gerhardt, M.B. et al. (1991). Removal of selenium using a novel algal-bacterial process. Res. J. Water Pollut. Control Fed. 63: 799–805. 30. Amweg, E.L., Stuart, D.L., and Weston, D.P. (2003). Comparative bioavailability of selenium to aquatic organisms after biological treatment of agricultural drainage water. Aquat. Toxicol. 63: 13–25. 31. Terry, N. and Zayed, A. (1998). Phytoremediation of selenium. In: Environmental Chemistry of Selenium. W.T. Frankenberger and R.A. Engberg (Eds.). Marcel Dekker, New York, pp. 633–655. 32. Fan, T.W.-M. and Higashi, R.M. (2000). Microphyte-mediated selenium biogeochemistry and its role in in situ selenium bioremediation. In: Phytoremediation of Contaminated Soil and Water. N. Terry and G.S. Banuelos (Eds.). CRC Press, Boca Raton, FL, pp. 283–302. 33. Higashi, R.M., Rejmankova, E.J., Gao, S., and Fan, T.W.M. (2003). Mitigating selenium ecotoxic risk by combining foodchain breakage with natural remediation. University of California Salinity/Drainage Program Annual Report. 34. Rofen, R. (2001). Agricultural evaporation ponds—source of marketable brine shrimp. Curr. Newlett. UC Center for Water Resources 2(2): 9–10.

SHELLFISH GROWING WATER CLASSIFICATION LINDA S. ANDREWS Mississippi State University Biloxi, Mississippi

Seafood-related illnesses in the United States are primarily associated with the consumption of bivalve

SHELLFISH GROWING WATER CLASSIFICATION

molluscan shellfish (1,2). As these animals are water filter feeders and are often consumed raw, the water that they are grown in affects their safety and quality. Bivalve molluscs feed by filtering microscopically sized particles out of the water. Via their inhalant siphon, they pump water through their gills. The gills sort out particles of the correct size and ‘‘feel’’ and direct them to their gut (3). The large volume of water that the bivalves pump through their siphons causes concern among public health officials. Consequently, it is imperative that water authorities, usually shellfish producer states, monitor the quality of water in and around the shellfish beds or reefs. For commercial markets, harvesting is only permitted from approved growing areas. The microbial acceptability of growing areas is classified on the basis of a sanitary survey of the shoreline to detect potential pollution sources and bacteriological analysis of water samples taken from the area (4). Shellfish sanitation programs originated at the national level in the United States in 1925 after a series of typhoid epidemics spread by the consumption of raw shellfish threatened the collapse of the oyster industry (3). Today, through the National Shellfish Sanitation Program, NSSP (5), State and federal public health regulators have established guidelines for water quality in shellfish growing areas to decrease the risk of illness associated with these seafood products. Sanitation surveys are normally performed by the state regulatory authority and include a written report of a shoreline survey, bacterial quality of the water, and an evaluation of the effect of any meteorological, hydrodynamic, and geographic characteristics of the growing area. Each surveying state maintains records of the surveys. For example, for Mississippi, survey results are filed with the Mississippi Department of Marine Resources (http://www. mississippiwebsite.com/deptmarinerec.htm). An analysis of the data from this survey determines the appropriate growing area classification. During shoreline surveys, the state authority identifies and evaluates all actual and potential sources of pollution to the growing area. If a pollution source exists, the distance from pollution to growing area is determined with an assessment of the potential impact. The effectiveness of sewage treatment and other wastewater treatment systems is evaluated for removal of the microbial and/or chemical contaminants. Comprehensive sanitation surveys for each growing area must be performed at least once every 12 years with triennial reevaluation based on water quality analysis and potential for any new sources of pollution. If this triennial evaluation determines that conditions have changed from the 12-year survey, the area in question may then be reclassified. On an annual basis, the sanitary survey shall be updated to reflect changes in the conditions of the growing area based on ‘‘drive through’’ surveys, observations made during routine sample collection, or information from other sources. In general, each growing area is classified as approved, conditionally approved, restricted, conditionally restricted, or prohibited based on the survey results (see Table 1). Status of a growing area is separate from its classification and may be either considered open or closed for

361

Table 1. Shellfish Harvest Area Classification Categories (5) Classification Approved

Conditional

Restricted

Prohibited

Growing areas are classified as approved when the sanitation survey finds the area safe for the direct marketing of shellfish or is not subject to human or animal fecal pollution. Growing areas are classified as conditional when the area in question is in the open status for a reasonable period of time and when pollution factors are predictable. There may be direct potential for distribution of pollutants based on unusual conditions or specific times of the year when bacterial numbers are increased by heavy water runoff that affects wastewater treatment plant function. Growing areas are classified as restricted when the sanitary survey indicates a limited degree of pollution and when levels of fecal pollution, human pathogens, or poisonous or deleterious pollutants are at such levels that shellstock can be made safe through either relaying or depuration. Growing areas are classified as prohibited when no current sanitary survey exists or when the survey determines that the growing area is adjacent to a sewage treatment plant outfall or other point source with public health significance or when the water is polluted because of previous or current sources of contamination.

harvesting of shellstock. All correctly classified growing areas are normally open for harvesting unless they are classified as prohibited. Closures may occur temporarily because of adverse weather conditions, the presence of biotoxins in concentrations of public health significance, or when the state authority fails to complete the written sanitary survey or triennial review evaluation report. A growing area may be placed into a remote status if the sanitation survey determines that the area has no human habitation and is not impacted by human pollution sources. The NSSP allows for a growing area to be classified using either a total or fecal coliform standard. Two sample collection strategies are used: adverse pollution condition and systematic random sampling. Each state authority may choose one of these sampling plans or use both depending on the location of the shellfish bed. Each state authority determines the number and location of sampling stations based on potential sources of pollution contamination as determined by the shoreline survey. Except for prohibited areas, the original or new classification of a shellfish growing area that has the potential to be impacted by a pollution source requires a minimum of 30 samples collected under various environmental conditions. For an area not impacted by a pollution source, 15 samples are required for initial classification. When using fecal coliforms (FC) as the

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indicator bacteria, the water quality must meet the following standards: FC median or geometric mean mostprobable-number (MPN) may not exceed 14 per 100 mL, with not more than 10% of samples exceeding 43 MPN per 100 mL for 5 tube decimal dilution or 49 MPN per 100 mL for 3 tube decimal dilution. When classifying point source growing sites, the bacterial quality of every station in the growing area must meet the fecal coliform standards as described above. Sample stations must be located adjacent to actual or potential sources of pollution. Refer to the NSSP Model Ordinance Chapter IV for details on sampling to achieve statistically reliable results (5). Separate standards are used for shellstock that will be processed by depuration posterior to harvesting. For the restricted classification of growing areas that are affected by point sources or nonpoint sources, FC median or geometric mean MPN of the water samples shall not exceed 88 per 100 mL and not more than 10% of the samples shall exceed an MPN of 260 per 100 mL for a 5 tube decimal dilution test or 300 MPN per 100 mL for a 3 tube decimal dilution test. Numerous factors are involved in interpreting FC data. Fecal coliforms are common as indicators of human fecal pollution and potential human fecal pathogens. However, pathogenic microorganisms typically do not occur in direct proportion to the number of FC present (3). This is especially true with viruses that move through tidal water at a much faster rate than heavier coliforms. Also, FC may die off at a rate different from other pathogenic organisms, thus giving a false sense of security that the shellfish are safe for human consumption. Another problem with using FC as an indicator of potential human pathogens is that FC may originate from sources other than humans. In rural areas, wild animals are likely to be the primary source of FC found in runoff. Major human pathogens of concern in shellfish waters usually originate on land, but exceptions include sewage discharges from boats and sewage treatment facilities. Runoff from land varies with rainfall, soil type, and degree of saturation. Consequently, one or even a few samples collected periodically may indicate very little about the pollution potential. Numerous samples collected under all weather conditions (heavy rain and high tides) are the only way to properly evaluate and classify a particular growing site. The restrictive rules for classification of shellfish growing waters have been established to provide the safest shellfish possible. All shellfish for human consumption are marked with a harvesters tag that indicates that they were harvested only from approved harvest areas. Today, illness outbreaks caused by the consumption of human pathogens that are present in raw molluscan shellfish are rare because of these rules for classification. BIBLIOGRAPHY 1. Anonyomous. (1988). Seafood Safety: Seriousness of Problems and Efforts to Protect Consumers. GAP/RCED-88-135, United States General Accounting Office, Washington, DC. 2. CDC. (1999). Morbidity and Mortality Reports. Center for Disease Control, Atlanta, GA. Available: www.cdc.gov.

3. Croonenberghs, R.E. (2000). Contamination in shellfishgrowing areas. Section VI, Seafood safety. In: Marine and Freshwater Products Handbook, pp. 665–696. 4. Cook, D.W. (1991). Microbiology of bivalve molluscan shellfish. In: Microbiology of Marine Food Products, pp. 19–39. 5. NSSP. (2002). Model Ordinance, Guide for the Control of Molluscan Shellfish, Chap. IV. U.S. Department of Health and Human Services, Public Health Service, Food and Drug Administration. Available: http://www.ISSC.org.

SORPTIVE FILTRATION K.A. MATIS N.K. LAZARIDIS Aristotle University Thessaloniki, Greece

INTRODUCTION Although filtration is one of the principal unit operations in the treatment of potable water, the filtration of effluents is less practiced; usual examples are supplemental removals of suspended solids from wastewaters of biological and chemical treatment processes and also the removal of chemically precipitated phosphorus (1). The available references dealing with filtration are quite voluminous—see, among others, the articles on filter presses, deep bed, cartridge, batch, variable volume, and continuous filters (2). Hence, the information provided in this section serves only as an introduction to the subject; for additional details, the literature should be consulted. In this article, no mention will be made of chromatographic applications (3). The seepage of rainfall and runoff into porous solids and rocks and the storage and movement of groundwaters in open-textured geologic formations are important elements in the resource and quality management of water and wastewater. Although fine-textured granular materials remove pollutants, the water drawn from them is acceptable only when natural filtration together with a time lapse between pollution and use bar the transport of pollutants to springs, wells, and infiltration structures (4). SORPTION A typical recent example of sorption is the removal of copper by suspended particulate matter from river water (5). Iron, silicon, and aluminum oxides were used as adsorbents, serving as models of naturally occurring suspended particles. On the other hand, sorption upstream of filtration constitutes a solution; the combined process has been also termed adsorptive filtration (6). In this module (offered by Separation Technologies), fundamental aspects of the process are illustratively given, such as inertial impaction and diffusional interception; however, the latter is effective only in gas filtration. Sorption, in general, is defined as a surface process irrespective of mechanism, adsorption or precipitation (7). Batch and column sorption studies of zinc, cadmium, and chromium were conducted on calcite to determine its

SORPTIVE FILTRATION

retention capacity for these elements common in industrial effluents and to explore its behavior as a purification filter in a continuous flow system (8). Fibrous carbon materials were examined for heavy oil sorption (9); oil spill accidents have caused serious problems in the environment, including disasters in living systems. Elsewhere (10), biologically active carbon (followed by ultrafiltration) was used for simultaneous sorption and biodegradation of organic constituents. Naturally occurring diatomaceous earth was tested as a potential sorbent for lead ions; the intrinsic exchange properties were further improved by modification with manganese oxides (11). Today, effective low-cost adsorbents for toxic metals are available; for instance, the case study to remove (by Metsorb adsorptive filtration media) depleted uranium from contaminated water at a U.S. Army testing site (12). In recent years, contamination of ground and surface waters with heavy metals has become a major concern. The knowledge of the oxidation state of pollutant ions is often a prerequisite for the application of efficient treatment methods, as in the case of arsenic. The inhibition of conventional metal precipitation due to the presence of chelating or complexing compounds, such as acetate, citrate, and tartrate ions, ammonia, and EDTA, which may be present in most real wastewater streams, is another problem for examination. Thermodynamic equilibrium diagrams and software packages (such as Mineql+) have been employed to construct aqueous speciation diagrams for the metals under investigation and, then, to interpret the removal mechanism involved. Sorption isotherm equations for equilibrium uptake, such as that of Freundlich and Langmuir, have been often used to fit the experimental data, and the activation energy of the process was calculated (13). Figure 1a presents some typical kinetic results for hexavalent chromium ions in batch sorptive removal under different conditions by (uncalcined) hydrotalcite as the appropriate sorbent, noting that desorption, particularly in successive stages, has received much less attention in the literature. The data were effectively fitted by a second-order kinetics equation. Another suitable (for metal cations) inorganic sorbent material is the group of natural or synthetic zeolites (Fig. 1b); the nonselectivity of the process is also apparent, sorbing zinc or calcium. Stress was given to electrokinetic measurements (expressed as zeta-potential) of the system

(a) 6

for its surface charge under the applied conditions to predict its behavior (14). The solution pH is important and influences metal speciation. So, for example, at pH lower than 6.8, corresponding to the pristine point of zero charge of α-FeOOH, the surface of these particles is positively charged. Therefore, in the pH range examined, the adsorption of anionic metal species was more pronounced (15). Fixed-Bed Sorption Ferric hydroxides, such as goethite, are another good example extensively studied; fixed-bed operation is the appropriate configuration for large-scale applications such as wastewater treatment (see Fig. 2a). The adsorbent material was granulated by crystallization through controlled freezing. Column adsorbers, due to pressure drop, require a suitable shape and size of the bonding material used. The experimental results are presented, expressed typically by the breakthrough curve concept, service time versus breakthrough (column outlet concentration related to the initial metal concentration—Coutlet /Cinitial ), as a percentage. In the inplots, the isoremoval lines of treatment time versus the respective quantity of sorbent are also presented at various breakthrough points. The major aim when sizing adsorptive columns is the ability to predict the service time until the column effluent exceeds a predefined solute (pollutant) concentration. The bed depth–service time model (abbreviated as BDST) relates the service time of a fixed-bed to the height of adsorbent in the bed, hence to its amount, because quantity is directly proportional to bed height. The measurement of sorbent quantity is more precise than the determination of the respective volume, especially for granules. Therefore, the sorbent quantity is preferably used instead of the bed height (15,16). Surface complexation models were used to describe metal cation adsorption on adsorbent materials; models, such as constant capacitance, diffuse layer, and triple layer were applied, showing that they could simulate experimental results. The fundamental concepts on which all these models are based remain, more or less, the same (17). The computer program PHREEQC (of the U.S. Geological Survey) permits a wide variety of aqueous geochemical calculations; surface-complexation modeling, applying mainly the diffuse double layer (DDL) model,

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Figure 1. (a) Time variation of chromium(VI) loading on hydrotalcite (1 g/L) at various eluant volumes. Reprinted with permission from Reference 13; copyright (2004) American Chemical Society. (b) Removal of calcium, zinc, or chromate ions (50 mg/L) by zeolites as a function of their concentration, at different pH values. Reprinted with permission from Reference 14; copyright (2004) Elsevier.

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is included in the program. The program uses a modification of the usually applied Newton–Raphson method iteratively to revise the values of the variables until a solution of the equation system is accepted within specified tolerances. A limitation of the program may be that uncertainties occur in determining the number of sorption sites, the surface area, the composition of sorbed species, and the appropriate surface-complexation constants. It was demonstrated that some of the surface complexation model (SCM) parameters might be incorrect due to an experimental artifact, though they give good simulations of data. This may be due to the success of least-squares fitting programs, such as FITEQL, in finding model parameters to describe experimental data sets. The results of the model, according to surfacecomplexation reactions and constants (see Table 1), are presented in Fig. 2b, in comparison with the experimental data for arsenic(III) oxyanions; they show good agreement, although the diffusion effects (external, or liquid film, and intraparticle transport resistance) were not taken into consideration (18). Similar conclusions were obtained with As(V). The arsenic problem is of particular concern

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Reaction Constants, log K 34.44 34.74 25.52 13.41

Surface-Complexation Reaction Goeth OH + H3 AsO3 = Goeth H2 AsO3 + H2 O a

4.51

Reference 18.

for small communities in rural areas around the world (a characteristic case is that of Bangladesh), where groundwater comprises the main drinking water source. Arsenite is favored under reducing (i.e., anaerobic) conditions. In this Encyclopedia, refer to another article on SORPTION KINETICS in the chapter on Physics and Chemistry of Water. For a number of ion exchangers of ultrafine particle size (for efficient use in packed column beds), a convenient binding polymer, such as modified polyacrylonitrile, has been used. The resulting sorbents were tested for separation and preconcentration of different contaminants, including radioactive wastes. The sorption characteristics of these composite materials were not affected by the binding polymer, whereas their physicochemical properties (hydrophilicity, mechanical strength, etc.) can be modified by the degree of cross-linking of the polymer, the use of suitable copolymers, or by changing the composition and temperature of polymerization (19). Certainly, an alternative to facilitate their solid/liquid separation downstream, particularly if fine adsorbents are to be dispersed, is to apply flocculation (20); note that many low-cost synthetic sorbents are produced as powders. THE COMBINED PROCESS

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Figure 2. (a) Breakthrough curves for goethite (at different quantities) and chromates; as an inset, isoremoval lines for 20%, 35%, and 50% breakthrough. Reprinted with permission from Reference 15; copyright (2001) Elsevier. (b) Sorption of trivalent arsenic on goethite mineral: experimental vs. theoretical (DDL modeling) values. Reprinted with permission from Reference 18; copyright (1999) Kluwer.

Liquid-phase carbon adsorption is a full-scale technology in which groundwater is pumped through one or more vessels containing activated carbon to which dissolved organic contaminants adsorb (21). When the concentration of contaminants in the effluent from the bed exceeds a certain level, the carbon can be regenerated in place; removed and regenerated at an off-site facility; or removed and disposed of. Carbon used for explosiveor metal-contaminated groundwater probably cannot be regenerated and should be removed and properly disposed of. Adsorption by activated carbon has a long history of use in treating municipal, industrial, and hazardous wastes. Figure 3a illustrates a sorptive filtration system. Another innovation has been proposed by introducing a two-stage process in a compact microfiltration (MF) hybrid cell (Fig. 3b). A large number of techniques have been used to limit membrane fouling; among them is air bubbling that also constitutes the transport medium in flotation, as applied in wastewater treatment; flotation is

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suitable as a pretreatment stage for microfiltration. The former accounted for around 90% solids removal. Ceramic flat-sheet membrane modules of multichannel geometry were used in this cell. The objective was to apply microfiltration by submerged membranes for efficient separation of metal-loaded zeolites. By this hybrid process, low residual metal concentration in treated water at maximum water yield and a higher concentration of metal bonding agent in the concentrates can be achieved (22). During the experimental series of continuous-flow separations by the membranes, all samples collected showed 100% zeolite recovery due to membrane filtration, hence, efficient solid/liquid separation. The metal (zinc) removal depended only on the amount of zeolite sorbent used; the remaining process parameters, examined in detail, had absolutely no influence on the former. One of the early notable investigations of adsorptive filtration is that by the EPA (23) at Superfund sites, those sites classified as uncontrolled and abandoned places where hazardous waste is located, possibly affecting the local ecosystem or people. In this application, toxic metals were removed by attachment to a thin layer of iron oxides that were immobilized on the surface of an appropriate filter medium, such as sand grains.

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An alternative sorbent that has been tried quite extensively is microbial biomass (24). The reason is that thousands of tons of residual biomass are produced each year from the fermentation, pharmaceutical, and chemical (i.e., citric acid biosynthesis) industries and also from biological wastewater treatment plants. The bacterial cell surfaces are known to be anionic, due to ionized groups in the various cell wall polymers. From a comparison of biosorption and other metal separation methods, such as filtration and centrifugation, it was found that the former favors the removal efficiency and applicability at lower (acidic) pH. In these conventional processes, metal cation removal is mainly due to their precipitation as hydroxides from pH alteration; this is presented in Fig. 4a showing a pH front/edge moving to the right toward alkaline values; precipitation was

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followed by flotation with dodecylamine as a surfactant. Of course, in sorption, metals are bonded on dead biomass (Streptomyces rimosus). Oxidation processes leading to insoluble products can also be mediated by specific bacteria, for example, for Mn(II) and Fe(II) (25); in these papers, from our lab, upflow filtration units were tested. One of the objectives was to obtain low sludge volumes, which often depends upon the method of precipitation. Upflow filtration has a theoretical advantage because coarse-to-medium filtration can be achieved by a single medium (such as sand) with almost perfect gradation of pore space and grain size from coarse to fine in the direction of flow. The bed is backwashed in the same direction but at higher flowrates, so the desired relative positions of fine media are maintained or reestablished by each run (1,4,26). The shortcomings of upflow filtration were overcome by using floating filter media. This type of filter can be backwashed with minimum water consumption and at lower rates. It also appeared from the laboratory experiments that metal removal was not limited by the solubility of the respective zinc hydroxide but by the effectiveness of the subsequent solid/liquid separation method (Fig. 4b). This semibatch unit, consisting of two columns in series and external recirculation of the filtered wastewater from the unit to the feed tank, was suitable for small- to medium-scale applications. In conclusion, sorptive filtration presents a promising technique. Today, there is a tendency for combined and compact processes, offering both the capacity for effluent treatment for environmental reasons, plus the recovery of metals that otherwise would be lost and, more importantly, water reuse. Acknowledgments Thanks are due to Dr. A.I. Zouboulis (AUTh) and Prof. A. Grohmann (WABOLU, Berlin) for their help.

BIBLIOGRAPHY 1. Metcalf & Eddy Inc. (1991). Wastewater Engineering: Treatment, Disposal, Reuse. Revised. McGraw-Hill, Singapore, p. 248. 2. Purchas, D.B. (Ed.) (1977). Solid/Liquid Separation Equipment Scale-Up. Uplands Press, Croydon, U.K., pp. 289, 319, 365, 445. 3. Wankat, P.C. (1986). Large-Scale Adsorption and Chromatography. CRC Press, Boca Raton, FL. 4. Fair, G.M., Geyer, J.G., and Okun, D.A. (1968). Water and Wastewater Engineering. John Wiley & Sons, New York, Vol. 2, p. 27–1. 5. Grassi M.T., Shi B., Allen H.E. 1997. Sorption of copper by suspended particulate matter, Coll. Surf. A 120: 199–203. 6. Univ. Pretoria, accessed 2004. Training module, Principles of Filtration, site: http://www.up.ac.za/academic/chemeng/ Facilities/Tribology presentations/05aSepTech.pdf. 7. Sposito, G.A. (1984). The Surface Chemistry of Soils. Oxford University Press, Oxford. ´ ´ 8. Garc´ia-Sanchez, A. and Alvarez-Ayuso, E. (2002). Sorption of Zn, Cd, and Cr on calcite. Application to purification of industrial wastewaters. Miner. Eng. 15: 539–547.

9. Inagaki, M., Kawahara, A., Nishi, Y., and Iwashita, N. (2002). Heavy oil sorption and recovery by using carbon fiber felts. Carbon 40: 1487–1492. 10. Pirbazari, M., Ravindran, V., Badriyha, B.N., and Kim, S.H. (1996). Hybrid membrane filtration process for leachate treatment. Water Res. 30: 2691–2706. 11. Al-Degs, Y., Khraisheh, M.A.M., and Tutunji, M.F. (2001). Sorption of lead ions on diatomite and manganese oxide modified diatomite. Water Res. 35: 3724–3728. 12. HydroGlobe, Inc., accessed 2004. Site www.hydrogobe.com 13. Lazaridis, N.K., Pandi, T.A., and Matis, K.A. (2004). Chromium(VI) removal from aqueous solutions by Mg-Al-CO3 hydrotalcite: Sorption–desorption kinetic and equilibrium studies. Ind. Eng. Chem. Res. 43: 2209–2215. 14. Zamboulis, D., Pataroudi, S.I., Zouboulis, A.I., and Matis, K.A. (2004). The application of sorptive flotation for the removal of metal ions. Desalination 162: 159–168. 15. Lehmann, M., Zouboulis, A.I., and Matis, K.A. (2001). Modelling the sorption of metals from aqueous solutions on goethite fixed-beds. Environ. Pollut. 113: 121–128. 16. McKay, G. (1996). Use of Adsorbents for the Removal of Pollutants from Wastewaters. CRC Press, Boca Raton, FL. 17. Dzombak, D.A. and Morel, F.M.M. (1990). Surface Complexation Modelling: Hydrous Ferric Oxide. John Wiley & Sons, New York. 18. Matis, K.A., Lehmann, M., and Zouboulis, A.I. (1999). Modelling sorption of metals from aqueous solution onto mineral particles: The case of arsenic ions and goethite ore. In: Natural Microporous Materials in Environmental Technology. P. Misaelides, F. Macaˇsek, T.J. Pinnavaia, and C. Colella (Eds.). Kluwer Academic, The Netherlands, pp. 463–472. ˇ 19. Zouboulis, A.I., Matis, K.A., Loukidou, M., and Sebesta, F. (2003). Metal biosorption by PAN-immobilized fungal biomass in simulated wastewaters. Coll. Surf. A 212: 185–195. 20. Matis, K.A., Zouboulis, A.I., Mandjiny, S., and Zamboulis D. (1997). Removal of cadmium from dilute solutions by hydroxyapatite. Part III. Flocculation studies, Sep. Sci. Tech. 32: 2107–2128. 21. Federal Remediation Technology Roundtable. Ex Situ Physical/Chemical Treatment (assuming pumping), site: http://www.frtr.gov. 22. Lazaridis, N.K., Bl¨ocher, C., Dorda, J., and Matis, K.A. (2004). A hybrid MF process based on flotation. J. Membrane Sci. 228: 83–88; (b) Matis, K.A., Bl¨ocher, C., Mavrov, V., Chmiel, H., and Lazaridis, N.K., Verfahren und vorrichtung ¨ zur membranunterstutzten flotation, Patents DE 10214457 C1 & EP 1354632 A1. 23. EPA (1993). Emerging technology summary: Metals treatment at Superfund sites by adsorptive filtration. EPA/540/SR93/515, Cincinnati, OH. 24. Zouboulis, A.I., Rousou, E.G., Matis, K.A., and Hancock I.C. (1999). Removal of toxic metals from aqueous mixtures: Part 1. Biosorption. J. Chem. Tech. Biotechnol. 74: 429– 436. 25. Katsoyiannis, I.A. and Zouboulis, A.I.: (a)(2002). Removal of arsenic from contaminated water sources by sorption onto iron-oxide-coated polymeric materials; (b) (2004). Biological treatment of Mn(II) and Fe(II) containing groundwater: Kinetic considerations and product characterization. Water Res. 36: 5141–5155; 38: 1922–1932. 26. Zouboulis, A.I., Lazaridis, N.K., and Grohmann, A. (2002). Toxic metals removal from waste waters by upflow filtration with floating filter medium. I. The case of zinc. Sep. Sci. Tech. 37: 403–416.

QUALITY OF WATER IN STORAGE

QUALITY OF WATER IN STORAGE PAULO CHAVES TOSHIHARU KOJIRI Water Resources Research Center Kyoto University, Japan

Water is our most precious natural resource. It is not only indispensable for the survival of all living beings but also has social and economic importance. It is no coincidence that most early human settlements were located near sources of freshwater. However, available water resources are increasingly under pressure from human population growth, increased standard of living, urbanization, and development of extensive areas for agriculture. As a result, available water may, at times, become insufficient to fulfill all the needs of human living, particularly during dry periods, which are caused by the natural randomness of the hydrological cycle. Therefore, it becomes necessary to find and to develop new sources of freshwater in order to secure a constant and appropriate supply of water. Certainly, many methods to maintain the stable supply of water exist, such as groundwater exploitation and water deviation from wet to dry areas. Undoubtedly, however, the most popular way worldwide to stabilize water supply is through the operation of stored water, particularly in lakes and manmade reservoirs. This concept was appreciated long ago, and reservoir construction has a long history, with the first dam believed to be built in ancient Egypt around 2800 B.C. (1). In the last few decades, most of these water storage systems have suffered from poor water quality, mainly caused by human activities within their watersheds and inefficient operation of these reservoirs. Although a variety of techniques to improve water quality in storage exist, most are either very costly or not sustainable. Therefore, efforts to find new methods to achieve better water quality are extremely important. One way is by taking advantage of the close relationship between quality (limnological) and quantity (hydrological and climatological characteristics) of water to better manage stored volumes to yield optimal benefits for water use while at the same time improving its quality. In the following sections, the main issues that impact on the quality of water in storage are presented. First, the important relationship between quantity and quality of water, and the potential improvement of water quality through the proper operation of storage volumes are highlighted. Then, the main issues related to evaluation of water quality are explained, showing the importance of proper water quality for different uses. Finally, all these topics are combined within the storage management and operation framework when water quality is considered. WATER QUALITY AND STORAGE Manmade reservoirs and lakes used for water storage, like other water bodies, are vulnerable to increasingly

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frequent problems of water quality. Some of the most common problems concerning the quality of water in storage are organic pollution, anoxia (deficiency in oxygen), eutrophication (increase of phytoplankton because of high nutrient concentrations), toxicity, turbidity, siltation, and waterborne diseases. In the same way, a variety of different possible causes of these problems exist, such as industrialization, increase of population, overexploitation of agricultural land, bad farming practices, poverty, lack of proper sanitation systems, runoff from cities, deforestation, lack of proper enforcement of the regulations for pollution control, and overuse of water resources with decrease of water volumes and levels. Probably, the most effective method to control pollution and improve quality of water in storage is through comprehensive watershed management, which includes reduction and control of nonpoint and point sources of pollution, such as nutrient and organic matter loads. On the other hand, other techniques exist that may be applied directly to the water bodies themselves, such as artificial mixing, aeration, sediment removal, chemical manipulation, algaecides, and biomanipulation of species like fishes and aquatic plants. However, most of these techniques are costly and difficult to implement. Basically, three main components of a reservoir system exist: inflow, storage, and release. Inflows may be defined as natural events, whereas storage and release may be considered under human control. Nevertheless, both natural variability and human decision can greatly influence the water quality of a reservoir. Reservoirs tend to present water of different quality during wet and dry hydrologic periods. With the increased runoff during periods of rain, higher nutrient loads would be expected in the reservoir, and these nutrients stimulate algae blooms and, therefore, may lower the water quality. Moreover, higher levels of inflow may also increase the inputs of organic matters resulting in dissolved oxygen (DO) depletion, which is defined as the decrease of dissolved oxygen concentrations, vital for sustaining aquatic life. On the other hand, higher inflows increase flushing rates and enhance mixing characteristics, decreasing stratification and potentially improving water quality. Hydrological factors, however, are not the only influences on water quality. Climatologic characteristics also play an important role, because during warm periods a higher probability of reservoir thermal stratification exists, because of a difference in temperature between water layers, leading to a difference in water density. The phenomenon of stratification, defined as the difference in density through the water column, which is commonly caused by variations of temperature, restricts the mixing of water between different layers. The isolated lower layer, called hypolimnion, can suffer from DO depletion by anaerobic processes and an increase in nutrients and other materials from bottom sediments. Water quality is closely tied to storage volumes. Clearly an increase of water volume results in increased dilution of pollutants, but, in addition, other physical, chemical, and biological processes that influence the quality of water may be closely related to controllable hydrological factors, such as the variation of release discharge, storage

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volumes, and water levels. For example, an increased retention time (defined as the ratio between reservoir volume and discharge rate) can influence water quality in many ways, such as decreasing mixing proprieties, increasing phosphorus retention, increasing the difference between surface-bottom temperatures (stratification), and decreasing turbidity that can enhance chances of algae bloom. Moreover, fluctuation of water levels may also enormously affect water quality, such as increased erosion from the shores that may result in higher turbidity, increasing washout of margins, and decreasing reproduction of some fish species (that lay eggs on coastal vegetation), consequently changing the phytoplankton (algae) population of the aquatic system. The quality of stored water may also be affected by the release of water with poor quality from different levels, such as bottomspillway discharge. Zalewski et al. (2) emphasizes the importance of ecohydrology to use ecosystem properties as management tools for sustainability of water resources, such as through adequate management of quantities to improve water quality. Moreover, his paper presents an example of the relationship between storage levels and the eutrophication process for the Sulejow Reservoir. Straskraba and Tundisi (3) discuss, in a general way, many aspects related to the management of reservoir water quality, such as ecotechnologies, relation between storage and water quality, and the possible impacts of different volumes and quality of discharged water from reservoirs. Therefore, the proper operation of release discharges and storage volumes considering single or multiple outlets and offtakes can also be considered an efficient method to improve the quality of stored water, by discharging water of undesirable quality or by increasing the storage volume with additional water, hence diluting water of poor quality (4,5). Although some general idea of the relationships between hydrologic and climatologic variables and water quality condition could be described, it is not possible to make a definitive statement about such relations. Specific studies for each reservoir system are needed to truly understand its limnology characteristics. Such studies need to include data collection and analysis, application of mathematical models, biological and hydrologic investigations, and, lastly, an understanding of the socioeconomic characteristics of the reservoir basin. Mathematical models can play an important role in the decision-making process, as these tools may support the decision makers in making the ‘‘best’’ decisions. The outcome of different decisions may be simulated and explored virtually with relatively low costs and in a short period of time. For more detailed explanation behind the mathematics of physical, chemical, and biological concepts of the quality models, the readers are referred to Jorgensen (6), Orlob (7), and Thomann and Mueller (8). WATER QUALITY EVALUATION Water quality directly affects virtually all water uses. Fish survival, diversity, and growth; recreational activities; corrosion of turbines of hydropower plants; municipal, industrial, and domestic water supplies; agricultural

uses like irrigation and livestock; waste disposal; and general aesthetics are all affected by the physical, chemical, biological, and microbiological conditions that exist in water bodies. Some water uses can affect water quality, which can influence other water uses. For instance, navigation may cause increased bank erosion leading to accelerated loss of storage volumes (reservoir sedimentation) and higher water turbidity. Water bodies used for wastewater assimilation may suffer from depletion of DO, which is required to sustain aquatic life, and an increase in total dissolved solids (TDSs), which is highly relevant to water supply, as higher TDSs increase treatment costs. The minimum acceptable quality of water depends very much on the water use itself. Water for irrigation, for example, should be low in dissolved salts, but water intended for livestock should be low in bacteria. Water used in industrial processes should usually be of a much higher quality than water used for industrial cooling. As for municipal supply, water must not only be safe to drink, but ideally should contain low concentrations of materials such as calcium and iron, as they may cause costly infrastructure damage or add unpleasant characteristics to the water even after treatment (9). A water quality index may be an efficient way to objectively measure water quality using a vast number of existing water quality parameters, helping decisions to be taken in a more efficient and less subjective way. Many of the water quality indices tend to be developed based on local characteristics and local expertise (10). Water quality indices may also be developed to express the conformity or net benefits of a water body with regard to a particular type of water use. In this scenario, different indices may be developed for the evaluation for a specific use or of the natural state of the system, such as for domestic drinking water supply, recreational use, wildlife preservation, trophic state situation (measure of eutrophication), and toxicity levels of water. Indices can be based on a single quality parameter or can even be presented as a combination of many quality parameters, such as the well-known Water Quality Index developed by the U.S. Environmental Protection Agency (EPA). Therefore, their use in the management and operation framework has to be closely studied and discussed among all stakeholders involved in the decision-making process. As a result of the vagueness involved in defining these indices, some new attempts have been made to evaluate water quality using fuzzy theory, such as in works by Norwick and Turksen (11), Dombi (12), and Chang et al. (13). MANAGEMENT OF STORAGE WATER QUALITY Water volume has always been a prime consideration in the design and construction of storage reservoirs, but quality has not. In the same way that quantity is regulated, water can be stored and released for the improvement of water quality and net benefits. As described in the previous sections, assessment, evaluation, and modeling of water quality are very complex tasks for water resource

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managers. Some of the reasons why water quality is still being left out from the decision-making framework process include: • Multiple stakeholders and multiple objectives are present in most cases. • A large number of physical, chemical, and biological water quality parameters exist to be considered. • Quality conditions present great spatial and temporal variability. • It is difficult to economically evaluate water and environmental quality. • Quality may be highly influenced by human activities and natural conditions. • Complete and representative spatial and temporal water quality data are seldom available. • Water quality simulation is a complex task because of the high levels of uncertainty involved in this process. The uncertainties when analyzing water quality are much greater than when dealing with water quantity. Uncertainty may strongly affect water quality management and the decision-making process of storage operation. However, from where does uncertainty come? Basically, uncertainty is inherent to many processes, such as measurement, natural randomness, and human perception. In a more concrete way, some sources of uncertainties assessing water quality include: • Construction problems of treatment facilities • Structures and parameters of a simulation model • Uncertainty of mismeasurement and incomplete data sets • Future and changing conditions (e.g., new socioeconomic activities in the watershed, global warming) • Vagueness of objectives (e.g., ‘‘improvement’’ of water quality) • Situations of accidents and disaster (e.g., traffic accidents or chemical leakage from factories) • Natural randomness of climate and hydrological variability (e.g., extreme events such as floods or long drought periods) Proper identification of the system uncertainties can support a more flexible and effective management framework, where components identified with greater uncertainty are considered for further investigation and the ones with less uncertainty may become more important decision tools, as the consequences can be more accurately predicted. Moreover, it may increase the public acceptance of a certain decision regarding reservoir management. Results after uncertainty analysis can be given in different ways, such as probability density function and confidence intervals, giving a range of possible outcomes avoiding the common ‘‘unexpected’’ results. Moreover, information on cost is frequently needed to improve the water quality management prior to the water quality impact assessment. Such costs may be related to water treatment; penalties for excessive pollution; socioeconomic losses, such as associated with tourism

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activities; and decrease of benefits of certain objectives when a multipurpose operation is considered. The operation of single and multiple outlet reservoir systems can present different objectives, such as improvement of water quality in stored volumes, released discharges, and intake water. Moreover, the management horizon can be specified to deal with different problems, such as related to the long-term planning, real-time operation, and emergency situations. Management of water quality can be considered together with the various types of reservoirs that may present different water use, such as reservoirs for water supply, irrigation, hydropower generation, flood control, recreation, and, of course, multipurpose systems. As explained previously, for each type of reservoir, a different evaluation method may be necessary. Besides the improvement of water quality condition itself, many advantages to considering water quality in the operation process exist, such as wider acceptance of reservoirs among the general public, decrease in maintenance costs, increase in net benefits, preservation of aquatic life, and achievement of sustainable policies. Straskraba and Tundisi (3) present many management models that combine quality simulation with management tools. Research in this field is in constant development, and some of the new models are imbedded with complex components, such as remote sensing information, geographic information system (GIS), management and optimization techniques, artificial intelligence (AI), and decision support systems (DSSs). It seems that much still exists to be accomplished and developed in the field of water quality in storage. The focus should be on integrated quality management, which must consider quantity and quality along with the three main components of a storage reservoir system: inflow, storage, and release. Moreover, other topics should be considered such as simultaneous combination of stochastic optimization and water quality simulation models, including uncertainty analysis, multiple water quality parameters in a multiobjective optimization framework, and multipurpose reservoirs considering the different stakeholders and water uses. The potential success in solving water quality related problems will depend on the ability of different professionals, including researchers, hydrologists, limnologists, and decisionmakers, to work together in an interdisciplinary and holistic manner. BIBLIOGRAPHY 1. Biswas, A.K. (1970). A History of Hydrology. North Holland Publishing, Amsterdam. 2. Zalewski, M. et al. (1997). Ecohydrology: A New Paradigm for Sustainable Use of Aquatic Resources. UNESCO, Paris, France. 3. Straskraba, M. and Tundisi, J.G. (1999). Guidelines of Lake Management—Reservoir Water Quality Management. Vol. 9. ILEC, Japan. 4. Welch, E.B. and Patmont, C.R. (1980). Lake restoration by dilution, Moses Lakes, Washington. Water Res. 14: 1317–1325.

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5. Chaves, P., Kojiri, T., and Yamashiki, Y. (2003). Optimization of storage reservoir considering water quantity and quality. Hydrol. Processes 17: 2769–2793. 6. Jorgensen, S.E. (1983). Application of Ecological Modeling in Environment Management. Elsevier, Amsterdam. 7. Orlob, G.T. (1983). Mathematical Modeling of Water Quality: Streams, Lakes and Reservoirs. John Wiley & Sons, Chichester, UK. 8. Thomann, R.V. and Mueller, J.A. (1990). Principles of Surface Water Quality Modeling and Control. HarperCollins Publishers, New York. 9. Kiely, G. (1997). Environment Engineering. McGraw-Hill, Berkshire. 10. Thanh, N.C. and Biswas, A. (1990). Environment—Sound Water Management. Oxford University Press, Oxford, UK. 11. Norwick, A. and Turksen, I. (1984). A model for the measurement of membership and consequences of its empirical implementation. Fuzzy Sets Syst. 12(1): 1–25. 12. Dombi, J. (1990). Membership function as an evaluation. Fuzzy Sets Syst. 35: 1–21. 13. Chang, N.B., Chew, H.W., and Ning, S.K. (2001). Identification of river water quality using the fuzzy synthetic evaluation approach. J. Environ. Manag. 63: 293–305.

QUALITY OF WATER SUPPLIES XINHAO WANG DIANA MITSOVA-BONEVA University of Cincinnati Cincinnati, Ohio

Adequate quantity and quality of water are necessary for human living and activities. A broad definition of water supply includes any quantity of available water. A more restricted concept of water supply refers to water collected and distributed to the general public or to other public or private utilities for residential, commercial, and industrial use. An even narrower definition of water supply only includes the water collected and conveyed for use in a community or a region (1). In the discussion here, water supply refers to water from the process of collection and distribution to meet human demand.

WATER RESOURCES Water resources are renewable but finite and scarce. As shown in Fig. 1, 97.22% of earth’s water is captured in oceans. Its total volume is enormous—1.3 billion cubic kilometers—but inadequate for human consumption because of the salt content. Approximately 2% of water is locked up in polar icecaps and glaciers. Water found in land, including surface water and groundwater, makes up less than 1% of the earth’s water resources (2). Groundwater is found in aquifers, moistureladen strata where water fills the spaces between rock particles. Although only about half of groundwater can be economically withdrawn for human use, it represents more than 97% of the usable freshwater resources. In addition, groundwater is a major source of replenishment for surface water. WATER CONSUMPTION Human water consumption consists of three major categories—agricultural, industrial, and domestic water use (3). According to the Food and Agriculture Organization of the United Nations (FAO), agricultural use accounts for 70% of global water withdrawals, while industrial and municipal use account for another 20% and 10%, respectively (4). Farming withdraws large amounts of water from rivers, lakes, reservoirs, and wells in order to irrigate crop fields and sustain plant growth in agricultural and horticultural practices. Almost 60% of the world’s freshwater withdrawals are used for irrigation purposes. In Asia, irrigated agriculture averages approximately 82% of all water consumption. The proportion in the United States is 41% and about 30% in Europe (5). Irrigation water is applied through irrigation systems for the purposes of field preparation, preirrigation, application of chemicals, weed elimination, dust reduction, plants cooling, frost protection, leaching salts from roots, and harvesting. Irrigation water is also used by golf courses, parks, nurseries, turf farms, and cemeteries. Industry consumes the second largest amount of water. In heavily industrialized regions, the percentage could

Earth water distribution Icecaps, glaciers 2.15%

Land 0.64%

Usable fresh water resources Fresh-water lakes Rivers 2.91% 0.03%

Atmosphere 0.00%

Shallow groundwater 97.06% Oceans 97.22% Oceans

Icecaps, Glaciers

Land

Atmosphere

Rivers

Fresh-water lakes

Figure 1. Earth’s water resources.

Shallow groundwater

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be much higher. In Europe, industry accounts for 52% of the total water consumption and in North America, 44% (6). Almost one-half of the industrial withdrawals are utilized for generating thermoelectric power with steamdriven turbine generators. Much of the industrial water is used for purposes such as cooling and is returned to its source. Large amounts of water are required also by food processing and paper producing industries, oil refineries, and chemical and metallurgical plants. Domestic water usage accounts for the last 10% of the total water consumption. This category refers to domestic consumption of water for drinking, hygiene, and other household uses, as well as commercial and institutional uses. The consumed domestic water is collected and treated in wastewater treatment plants before being discharged back to a natural water body. TYPES OF WATER SUPPLY Water supply systems refer to private (self-supplied, such as private wells) or public (may be operated by public agencies or private companies) withdrawals from ground and surface water designated to serve specific users. The most common is the public or municipal water supply system, which provides water to domestic, public, and commercial users and, occasionally, to industries, hydroelectric and thermoelectric plants, or for irrigation (7). The majority of the population throughout the world, especially urban population, is served by public water supply systems. Figure 2 illustrates the average percentage of the large city population served by each type of water supply service, by region. Household connection or yard tap and public tap are public water supplies. In the more developed regions, such as Europe and North America, more than 96% of the urban population has household connection to public water supply services. In Africa and Asia, considerable numbers of people are not served by public water supply systems. QUALITY OF WATER SUPPLY Water is an excellent solvent that can dissolve many elements. The amount of each element affects water quality, reflected in the chemical, physical, or biological condition of water. Therefore, water quality is often measured with what is contained in water, such as dissolved oxygen, suspended solids, pesticides, metals, oils, minerals, and nutrients. Pathogenic bacteria might affect human and animal health and so they are often measured. Physical conditions are another set of water quality measurement, such as water temperature, water color, and turbidity. Water quality also can be assessed with biological indicators, which measure the type and diversity of fish, macroinvertebrate species, and plants (9). Some uses of water for industrial activities, such as mining, cooling water supply, washing, fire protection, or oil well repressurization, may not depend on water quality. Different industries may have different requirements for water quality, such as the turbidity or temperature. Normally, industrial water use does not require filtration and chlorine treatments.

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Quality criteria for irrigation water include measurements of its salinity, alkalization, toxicity, and electrical conductivity. Salinity indicates the presence of high concentrations of chloride, sulfate, and bicarbonate compounds of sodium, calcium, and magnesium. In regions with significant rainfalls, those soluble salts are flushed out from the crop root zone on a regular basis. In arid and semiarid areas, water percolating through the soil is not sufficient to leach those salts. The increasing concentrations may adversely affect crops with low level salt tolerance thresholds. Therefore, irrigation waters must be controlled for their content of dissolved salts in order to prevent further deterioration of the soil quality and reduction of crop yields. There is a direct positive relationship between salt concentrations and the electrical conductivity of irrigation water. Alkalization occurs when the soil is more saturated with sodium than calcium and magnesium. Excess sodium results in high pH, reduced oxygen content, soil erosion, and less nutrient absorption by plants. Some constituents of the irrigation waters such as boron, chloride, and sodium are toxic to crops. Irrigation waters containing such chemicals are not recommended for use in watering soybeans, citrus, or grape plants (10). Water quality of domestic water supplies has a direct effect on human health. Microbial pathogens that are found to cause enteric diseases in humans include bacteria (such as Vibrio cholerae, Shigella, Salmonella, Campylobacter, and Escherichia coli), viruses (such as hepatitis A virus and rotavirus), and parasites (such a Giardia lamblia and Cryptosporidium). Bacterial waterborne infections include cholera, dysentery, salmonellosis, typhoid fever, ‘‘traveler’s disease,’’ and E. coli outbreaks. The most common viral disease contracted through contaminated water is hepatitis A. Sewage-tainted drinking water can also cause certain parasitic protozoan diseases such as amebic dysentery and giardiasis. Those diseases are usually contracted by drinking water or eating food contaminated with pathogens of fecal origin. They are characterized by severe diarrhea, vomiting, and cramps, and in some cases, by high fever, headache, and muscle pains. The most common cause of death associated with those ailments is rapid dehydration and subsequent collapse of the vascular system (11). Domestic water supply for drinking purposes is the most critical of all. The World Health Organization (WHO) estimates that each year approximately 2.5 million children all over the globe, ages 0–12, die of waterborne diarrhea illnesses. Waterborne diseases are the leading cause of death in most developing nations in Africa, Asia, and Latin America. Despite efforts to render safe drinking water to an increasing number of people, as a result of the unprecedented population growth, approximately 1.1 billion people still use unsafe drinking water (12). Water disinfection in the last century has largely reduced the incidence of infectious waterborne diseases. Health officials today and the general public, however, are more and more concerned about chronic health effects potentially caused by the presence of toxic chemicals in drinking water. Ingestion of even small amounts of some inorganic pollutants such as arsenic, lead, cadmium, chromium, mercury, asbestos, cyanide, or nitrates can

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QUALITY OF WATER SUPPLIES Africa

Others, 6%

Unserved, 31%

Household connection or yard tap, 43%

Asia Unserved 6%

Borehole or handpump, 5% Public tap, 7%

Others, 2% Public tap, 21%

Borehole or handpump, 3%

Household connection or yard tap, 77%

Household connection or yard tap

Public tap

Household connection or yard tap

Public tap

Borehole or handpump

Others

Borehole or handpump

Others

Unserved

Unserved Latin America & Carribean Others, 4%

Unserved 15%

Borehole or handpump, 1%

Oceania Borehole or Others, 3% handpump, 0% Unserved, 2% Public tap, 3%

Public tap, 3% Household connection or yard tap, 77% Public tap Others

Household connection or yard tap Borehole or handpump Unserved

Household connection or yard tap, 73% Household connection or yard tap

Public tap

Borehole or handpump

Others

Unserved Europe

Borehole or handpump, 1%

North America Others, 0% Unserved, 2%

Public tap, 1%

Household connection or yard tap, 96% Household connection or yard tap Borehole or handpump

Household connection or yard tap, 100%

Public tap

Household connection or yard tap

Public tap

Others

Borehole or handpump

Others

Unserved

Unserved

Figure 2. Water supply in the largest cities: average percentage of the population served by each type of service, by region (8).

cause a wide range of health problems. Especially vulnerable to lead poisoning are young children. Ingested lead can result in anemia, neurological disorders, kidney problems, sterility, and birth defects. Evidence suggests that exposure to even very low levels of asbestos in drinking water can result in cancers of the gastrointestinal tract. Although conclusive evidence about cause-andeffect link between chemical contaminants and cancers, birth defects, miscarriages, nervous and reproductive system disorders, and organ damage has not yet been

established, there is little doubt that prolonged exposure to some organic and inorganic substances can result in chronic health conditions. Nitrates are another inorganic chemical with serious health effects. The intake of nitratecontaining water by infants under the age of six months may cause methemoglobinemia, known also as the ‘‘blue baby syndrome’’ (13). The organic compounds detected in drinking water include a wide variety of herbicides and pesticides, disinfection by-products, PCBs, solvents, oils, and so on.

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They are volatile and nonvolatile in nature. Many of them are suspected carcinogens (14). Radionuclides are also known to be present in some drinking water supplies. The quality of the drinking water supplies in the United States is one of the highest on earth. With the adoption of the Safe Drinking Water Act in 1974, subsequently amended in 1986 and 1996, the U.S. Congress empowered the U.S. Environmental Protection Agency (U.S. EPA) to enforce regulations aimed at protecting the quality of drinking water supplies. The U.S. EPA has established two sets of standards for water quality: primary and secondary. The objective of the primary standards is to protect human health. They are based on toxicological, epidemiological, and clinical data. The maximum contaminant level (MCL) is the primary standard enforced by the U.S. EPA. Secondary drinking water standards refer to contaminants that create unpleasant odor, taste, and color or may be corrosive or staining. They can cause minor skin irritations or damage clothing and appliances (15). Table 1 displays the major contaminant categories, their potential health effects, and sources of contaminants in drinking water. FACTORS AFFECTING THE QUALITY OF WATER SUPPLY The quality of the water source is critical for the quality of water supply. Water pollution refers to the deteriorating

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quality of water due to the presence of pollutants in the water. Effluent discharges from industries and municipal sewage plants are considered point source pollution. They are relatively easy to identify, regulate, control, and monitor since they are usually located near factories, wastewater treatment plants, septic tanks, or stormwater outfalls. In the United States, industries discharging directly into rivers and lakes are required to apply for permits in accordance with the National Pollutant Discharge Elimination System (NPDES) program. The permit specifies the volume, type, and permissible concentrations of pollutants allowed to be released in the waterways. The other option for controlling industrial discharges is to reuse the treated wastewater instead of discharging it into receiving waters. Nonpoint source pollutants consist of suspended solids, nutrients, petroleum, inorganic, and radioactive compounds. A major contributor of sediment to the waterways is the runoff from agricultural fields and construction sites. Silt and soil increase the turbidity of water, which impairs the productivity of photosynthetic plants, reduces water depth, endangers bottom-dwelling animals, and suffocates fish. Nutrients enter waterways in the form of fertilizer and sewage runoff, leaves and grass, or as runoff from livestock farms and pastures. Many hazardous chemicals such as asbestos, hydrocarbons, PCBs, pesticides, mercury, and lead enter the waterways

Table 1. The U.S. EPA’s National Primary Drinking Water Standards Contaminant Microorganisms Disinfection by-products

Inorganic chemicals

Organic chemicals

Potential Health Effects from Ingestion of Water Gastrointestinal illness, legionnaire’s disease Increased risk of cancer, anemia; in infants and young children—central nervous system effects, liver and kidney problems; increased risk of cancer Increase in blood cholesterol; problems with circulatory system; increased risk of developing benign intestinal polyps; intestinal lesions; kidney damage; allergic dermatitis; nerve damage or thyroid problems; bone disease (pain and tenderness of the bones); delays in physical or mental development of infants and children Nervous system or blood problems; increased risk of cancer; eye, liver, kidney, adrenal gland, or spleen problems; anemia; cardiovascular system or reproductive problems; circulatory system problems; thymus gland problems; immune deficiencies

Sources of Contaminant in Drinking Water Human and fecal animal waste Human and fecal animal waste

Discharge from petroleum refineries; ceramics; erosion of natural deposits; runoff from glass manufacturing sites; decay of asbestos cement in water mains; erosion of natural deposits; discharge from metal refineries; corrosion of galvanized pipes; discharge from steel and pulp mills, plastic and fertilizer factories; water additive that promotes strong teeth; corrosion of household plumbing systems; erosion of natural deposits Added to water during sewage/wastewater treatment; runoff from herbicide used on row crops; leaching from gas storage tanks and landfills; leaching from linings of water storage tanks and distribution lines; leaching of soil fumigant used on rice and alfalfa; discharge from chemical plants, agricultural chemical factories, and other industrial activities; residue of banned termiticide; runoff from herbicide used on rights of way; runoff/leaching from soil fumigant used on soybeans, cotton, pineapples, and orchards; emissions from waste incineration and other combustion; discharge from wood preserving factories; discharge from rubber and plastic factories; leaching from landfills; discharge from factories and dry cleaners; runoff/leaching from insecticide used on cotton and cattle; discharge from textile finishing factories; breakdown of heptachlor; residue of banned insecticide

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through airborne deposition. Acid rainfall is a typical example of airborne pollution that affects the waterways. In addition to water quality at sources, the contamination of distribution pipelines may be a major concern for the quality of water supply. One cause of contamination is cross-connection, where there is a physical connection between a drinking water supply line and a source of contamination, such as viruses, bacteria, and nitrate. The materials of pipes could also be the source of contamination, such as lead dissolved from pipes and plumbing fixtures. TREATMENT OF WATER SUPPLIES A water supply system normally consists of facilities for water withdrawal, storage, treatment, and distribution. After treatment, water is usually resent into the distribution system or to water storage reservoirs (16). Water suppliers apply different types of treatment according to the type of water use and the quality of their source water. Some groundwater supplies can meet the standard requirements without any additional treatment. In most cases, however, and especially when it comes to surface water supplies, a combination of treatment methods is applied to remove contaminants from raw water. The first stage of the water treatment process is usually to settle the water in order to separate the large solid debris. During the process of chemical coagulation the synthetic organic polymers (cationic and anionic) are aplied to coagulate colloidal material. During flocculation, often preceded by rapid mixing, tiny particles combine into larger and heavier ‘‘flocs.’’ Sedimentation is used to reduce sediment loads in raw water both before and after flocculation. It allows for the removal of sand, silt, gravel, and alum floc. Some hard waters require an additional chemical treatment before filtration. Limesoda softening is applied to raw waters rich in calcium and magnesium. As in flocculation, softening converts hardness-creating ions into insoluble precipitates, which are then removed through settling and filtration. Some raw water supplies containing iron, manganese, and volatile organic compounds need to be treated by aeration. This

method allows for the oxidation of chemicals, formation of precipitates, and their subsequent removal by filtration. Filtration is mostly a physical process in which the water flows through beds of gravel, sand, anthracite, or diatomaceous earth. However, in order to increase its effectiveness, coagulants are also applied throughout the filtration process. Adsorption involves the application of activated carbon, which adsorbs nonvolatile organics and some taste- and odor-causing compounds. Ion exchange is used to remove inorganic chemicals (such as arsenic, chromium, or excess fluoride) as well as nitrates and radionuclides (17). Chlorination, ozonation, and ultraviolet radiation are methods used during the proccess of disinfection. Chlorination is very effective in killing bacteria but less effective in eliminating viruses and protozoans. However, it has the advantage to continue the process of disinfection in the distribution pipes. Ozonation and UV radiation have powerful germicidal effect but both have disadvantages. Ozone has a very short half-life and must be generated electrically at the point and at the moment of use. UV disinfection is applied through UV lamps, which allows for contamination (18). Figure 3 illustrates the process in a domestric water treatment plant in Cincinnati, Ohio (19). Desalination is not a typical water treatment method. However, in arid coastal areas or in regions with mounting pressure on existing freshwater resources, desalination is routinely used to transform seawater into potable water. Saudi Arabia is the leading producer of desalted water in the world. Two methods of desalination are usually applied. Smaller plants rely mainly on reverse osmosis, while larger producers use multistage flash distillation processes (20). PROTECTION OF WATER RESOURCES Rapid industrialization since the nineteenth century has been accompanied by reckless waste management practices, which had turned many surface water bodies into sewers or algae-coated cesspits containing microorganisms, toxic chemicals, heavy metals, organic pollutants, pesticides, fertilizers, and their by-products. In addition, these contaminants penetrate the soil, where they can

The treatment process at the miller plant on the ohio river Presettling removes most solids

Further settling occurs in reservoir

Final settling occurs, water prepared for final treatment Sand and gravel pH adjusted filter water

Granular activated carbon removes organics

pH adjusted again, chlorine added fluoride added Reservoir

Settling acids added

Ohio river

Miller plant treats 120 million gallons per day (average pumpage)

Intake

Furnace cleans carbon To for reuse distribution

Pumps

system

Figure 3. A domestric water treatment plant.

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reach the water table and deteriorate the quality of groundwater. Since most of the freshwater supplies rely on groundwater and the slow flow of groundwater, it is critical to keep groundwater from being contaminated. Both the United States and the European Commission have come to the conclusion that setting chemical quality standards for groundwater is not appropriate, as it creates the impression of an allowed level of pollution. The World Bank estimates that during the past century water consumption has risen sixfold, which is twice as fast as the rate of population growth. By the year 2025, four billion people, particularly in Africa, the Middle East, and South Asia, are expected to live under conditions of severe water stress, if appropriate actions are not taken (21). The total volume of water consumption also affects the quality of water supply. In order to keep the demand within the safe yield of the system, many cities are implementing water-saving policies and restrictions (22). Three major irrigation methods—sprinkler, microirrigation, and surface (flood)—are applied (23). In general, only a small portion of the irrigation water is actually reaching its intended target. The majority is transformed into vapor through the processes of evaporation and transpiration or is lost in transit (24). Many conventional methods should be supported to increase field water use efficiency and the crop productivity of unit water consumption. Through more efficient irrigating practices such as the automated drip irrigation, alternate irrigation in controlled root zones, and water-deficit-regulated irrigation can substantially reduce water demand in agriculture without reducing crop yield (25). Research has shown that comprehensive water-saving farming technology can increase irrigation productivity 10–15% (26). Water conservation approaches should also be applied in manufacturing and mining industries and in urban areas to establish a water-saving society. To do so, industrial wastewater should be treated and reused to increase the utilization ratio. Sustainable water resources will not only efficiently support the existing socioeconomic systems but will also provide the required quantity and quality of water at reasonable cost in the future (27). BIBLIOGRAPHY 1. The American Heritage Dictionary of the English language, 4th Edn. (2000). Houghton Mifflin, Boston. 2. U.S Geological Survey (2003). Water science homepage. Available at http://ga.water.usgs.gov/edu/earthwherewater.html. 3. World Resources Institute Database (2000). Available at http://earthtrends.wri.org/searchable db/index.cfm?theme =2. 4. Food and Agriculture Organization of the United Nations (FAO) (2003). Water Resources, Development and Management Service. AQUASTAT Information System on Water and Agriculture: Review of World Water Resources by Country. Available online at http://www.fao.org/waicent/faoinfo/ agricult/agl/aglw/aquastat/water res/index.htm. 5. Nadakavukaren, A. (2000). Our Global Environment, Waveland Press, Prospects Heights, NY. 6. World Resources Institute Database (2000). Available at http://earthtrends.wri.org/searchable db/index.cfm?theme =2.

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7. USGS National Handbook of Recommended Methods for Water Data Acquisition, Chap. 11. Available at http://water. usgs.gov/pubs/chapter11/chapter11C.html. Accessed 2004. 8. WHO Global Water Supply and Sanitation Assessment 2000 Report. Available at http://www.who.int/docstore/water sanitation health/Globassessment/Global4.3.htm. Accessed 2004. 9. U.S. EPA (2004). Monitoring and Assessing Water Quality Guidelines. Available at http://www.epa.gov/owow/ monitoring/elements/elements.html#d. Accessed 2004 10. Hoffman, G.J. (2004). Water quality criteria for irrigation, EC97-782, University of Nebraska, Institute of Agriculture and Natural Resources, issued in cooperation with the U.S. Department of Agriculture. Available at http://ianrpubs.unl.edu/irrigation/ec782.htm#sum. Accessed 2004. 11. WHO drinking water quality and infectious diseases transmission and prevention. Available at http://www.who.int/ water sanitation health/dwq/infectdis/en/print.html. Accessed 2004. 12. WHO Joint Monitoring Program Report (2004). Meeting the MDG drinking-water and sanitation target: a mid-term assessment of progress. Available at http://www.who.int/ water sanitation health/monitoring/jmp2004/en/. 2004. 13. National Sanitation Foundation (1991). Standard NSF 611991 Drinking water system components—health effects. 14. National Sanitation Foundation (1991). Standard NSF 611991 Drinking water treatment chemicals—health effects. 15. U.S. Environmental Protection Agency (2002). National Primary Drinking Water Regulations. Available at http://www. epa.gov/safewater/mcl.html. EPA 816-F-02-013. 16. Litke, D.W. and Kauffman, L.F. (1993). Analysis of residential use of water in the Denver metropolitan area, Colorado, 1980–87. U.S. Geol. Surv. Water Resour. Invest. Rep. 92–4030, p. 69. 17. Logsdon, G., Hess, A., and Horsley, M. (1999). Guide to selection of water treatment processes. In: Water Quality and Treatment—A Handbook of Community Water Supplies, 5th Edn. R.D. Letterman (Ed.). McGraw-Hill, New York, pp. 3.1–3.26. 18. Haas, C.N. (1999). Disinfection. In: Water Quality and Treatment - A Handbook of Community Water Supplies, 5th Edn. R.D. Letterman (Ed.). McGraw-Hill, New York, pp. 14.1–14.60. 19. Greater Cincinnati Water Works. Available at http://www. cincinnati-oh.gov/water/pages/-3283-/. 20. Encyclopedia of Desalination and Water Resources (1997). EOLSS Publishers Co. Ltd., UK. 21. World Bank Water Resources Strategy (2003). 22. Jenkins, M.W. et al. (2004). Optimization of California’s water supply system: results and insights. J. Water Resour. Plan. Manage. 130(4): 271–275. 23. U.S. Department of Agriculture, National Agricultural Statistics Service. Drought and Fire Survey 2000, Montana’s 2000 Drought/Fire Survey Results: press release. Available at http://www.nass.usda.gov/mt/pressrls/misc/firesurv.htm. Accessed June 25, 2003. 24. Hutson, S.S., Barber, N.L., Kenny, J.F., Linsey, K.S., Lumia, D.S., and Maupin, M.A. (2004). U.S. Geological Survey Estimated Use of Water in the United States in 2000. USGS Circular 1268, released March 2004, revised May 2004. 25. Kang, S. and Li, Y. (1997). The water economic trends and countermeasures for the 21st century. Acta Agric. Technol. 18: 32–36.

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26. Feng, P.G. (1997). Study of the principles of support for water resource sustainability and water economical utilization. Agric. Res. Arid Area 15: 1–7. 27. Loucks, D.P. (2000). Sustainable water resources management. Water Int. 25(1): 2.

THE SUBMITOCHONDRIAL PARTICLE ASSAY AS A BIOLOGICAL MONITORING TOOL FRANCIS G. DOHERTY AquaTox Research, Inc. Syracuse, New York

BACKGROUND While studies assessing the toxicity of environmental contaminants to aquatic organisms date back to the early 1900s, the use of toxicity testing as a tool for monitoring the environmental acceptability of discharges from wastewater treatment and manufacturing facilities to surface waters (i.e., rivers, lakes, and oceans) did not begin to evolve until the 1970s. One of the primary motivating factors behind the development of biological monitoring, or biomonitoring, was the manufacture of exponentially increasing numbers of new chemicals for which analytical procedures were generally lacking. Biomonitoring was viewed as an approach to detect the presence of potentially toxic chemicals in facility discharges without necessarily having to identify the contaminants at that stage of the assessment. Additional advantages included the reduced expense associated with biologically testing significantly greater numbers of samples in comparison with analytical procedures. This approach also focused on only biologically available forms of the chemicals in solution reflecting any interactive effects (synergistic or antagonistic) that might be occurring among contaminants within a complex sample. Initial research efforts in the biomonitoring field tended to focus on identifying a ‘‘most sensitive species’’ that satisfied a variety of other criteria. These criteria included, but were not necessarily limited to, widespread geographic distribution and ease of culture in the laboratory so as to provide a steady supply of consistently healthy test organisms. A significant amount of effort was also invested in the development of standardized protocols that focused on the control of test variables to provide guidance to laboratories conducting aquatic toxicity tests, thereby permitting direct comparisons of toxicity data from multiple sources. This preliminary round of research tended to use common endemic fish species (e.g., salmonids and cyprinids) and planktonic invertebrates (e.g., Cladocerans) that served as a food source for larval fish stages as the primary test species in whole organism assays. Lethality and growth or reproduction served as test endpoints. These efforts ultimately led to the development of acute (‘‘short-duration’’) and chronic (‘‘long-duration’’) standardized protocols most often employing the fathead minnow, Pimephales promelas, and the Cladoceran Ceriodaphnia

dubia for discharges to freshwater systems (1,2). Companion protocols were also developed for discharges to brackish and marine environments employing saltwater organisms. This initial focus, however, quickly and almost simultaneously expanded to include other less common fish and invertebrate species along with surrogate microorganisms and in vitro biochemical assays in a continuing attempt to identify that elusive ‘‘most sensitive species or assay.’’ Alternately, these activities addressed refining or enhancing existing protocols with the primary, preferred species. Other objectives included in this broad research effort included accelerating the pace at which analyses were conducted by primarily reducing the exposure time for standardized tests, which also resulted in a reduction in the cost of testing. SUBMITOCHONDRIAL PARTICLE ASSAY One such surrogate assay developed during the early to mid-1980s was the in vitro submitochondrial particle (SMP) assay (3–6). This assay exposes processed mammalian mitochondria to samples of interest and spectrophotometrically monitors the concentration of NADH to assess the level of ‘‘toxicity’’ exerted by contaminants present in the test solution. SMPs are prepared from bovine heart mitochondria according to the procedure detailed in Hansen and Smith (7). Briefly, the patented SMP production process involves sonically disrupting isolated mitochondria and separating the inner and outer membranes by differential centrifugation. The inner-membrane isolates retain more than 60 fully functional interacting enzymes associated with cellular electron transport and oxidative phosphorylation. Since the test system is in direct contact with test material, there are no physical barriers interfering with the interaction between the test material and receptors as there are in whole organism tests, thereby creating a potentially ultrasensitive assay. There are two distinct and functional complementary assays utilizing SMPs. The electron transfer (ETr) assay assesses forward electron transfer through the entire electron transport chain. The test endpoint is the loss of NADH monitored as a decrease in absorbance at 340 nm in a standard spectrophotometer using 1-cm path length disposable methyl acrylate cuvettes. The reverse electron transfer (RET) assay assesses effects on electron transfer and energy coupling processes. In this test, energy derived from the hydrolysis of ATP drives electrons in the reverse direction, up the electron transport chain. The test endpoint is the production of NADH also monitored at 340 nm on a standard spectrophotometer. Sample preparation and absorbance measurement patterns for the RET assay parallel that described for the ETr assay. Processed SMP and associated reagents for conducting tests are commercially available. Reagents for conducting the assays include SMP diluent for diluting particles to 1.5 mg/mL; RET and ETr concentrated reaction mixtures (CRM) containing buffer, electron donors (RET CRM only), and cofactors required by the SMP, adenosine-5triphosphate (ATP) for activating the RET reaction, and ß-nicotinamide adenine dinucleotide sodium salt, reduced

THE SUBMITOCHONDRIAL PARTICLE ASSAY AS A BIOLOGICAL MONITORING TOOL Table 1. Final Concentrations of Particles, Activating Agents, and Concentrated Reaction Mixture (CRM) Components for the Reverse Electron Transport (RET) and Electron Transport (ETr) Submitochondrial Particle (SMP) Assays SMP Particles Activating agents CRM components

RET 0.05 mg/mL 3.33 mM ATP 50 mM HEPES (pH 7.5) 6 mM Mg2+ 5 mM K+ succinate 1 mM NAD+

ETr 0.0167 mg/mL 0.137 mM NADH 50 mM HEPES (pH 7.5) 6 mM Mg2+

form (NADH 2Na+ ) for activating the ETr reaction. Unpublished data generated in the author’s laboratory has revealed that particles held at −80 ◦ C for up to six months remain fully functional. In contrast, some vials of particles held at −20 ◦ C for that same period of time exhibit a reduction to complete loss of activity that is not directly related to storage duration. The final concentrations of particles and reagents in the two assays are provided in Table 1. The objective of an individual test is to determine the median effective concentration (EC50 ): the concentration at which the rate of NADH loss (ETr) or production (RET) is twofold the rate observed in the control treatment. Individual rates of NADH loss or production (as expressed by the slopes of the lines-of-best-fit for each treatment) are determined by simple linear regression analysis for the relationship between time and the mean NADH concentration between replicates within a treatment. Individual slopes are then used to calculate percent inhibition values relative to the control treatment for each toxicant treatment. The EC50 for an individual test is determined from the linear portion of the regression of individual treatment percent inhibition values versus concentration. Determination of linearity (i.e., which points to include in the generation of the line-of-bestfit) is achieved through both qualitative and quantitative criteria. Plots are visually assessed to identify a linear portion to the curve and supplemented with the generation of coefficient of determination (R2 ) values to confirm the most consistent relationship among points to include in the lines-of-best-fit. The statistical analyses can be conveniently performed by routine spreadsheet software. EXISTING LITERATURE REVIEW Published studies assessing the sensitivity of SMPs to test materials can be segregated into two broad classes—those dealing with pure chemicals and those dealing with environmental samples. Studies focused on assessing the toxicity of pure chemicals did not directly relate to the use of SMPs for environmental monitoring. Rather, these studies for the most part simply attempted to demonstrate the potential for use of SMPs for biomonitoring by invoking the limitations associated with existing methods and comparing the sensitivity of the SMP assay with other more established tests. For example, Bragadin and

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Dell’Antone (8) cited the cost and duration of acute fish tests as motivation for the development of alternatives such as the SMP assay. They reported the EC50 values for a few dozen toxic compounds using a modified approach to the assay described above and concluded that the results from their assay compared favorably with published values of toxicity for other species that included rainbow trout and the commercial bacterial luminescent assay, Microtox . Similar approaches were adopted using the RET variant by Argese et al. (9) with linear alkylbenzene sulfonates, nonylphenol polyethoxylates, and their derivatives; by Argese et al. (10) with chlorophenols; by Argese et al. (11) with heavy metals; and by Argese et al. (12) with chloroanilines. Each study compared their in-house generated toxicity values from the RET variant of the SMP assay with published literature values for other species, and in general concluded there were significant levels of correlation with many of the existing assays. Researchers associated with the development of the SMP assays also published their own results with a substantial set of diverse chemicals (n = 162) tested with one of the SMP assay variants while comparing toxicity values with published endpoints for other species (13). Their conclusions mirrored those of other researchers in this field while they also summarized other current issues related to the state of the SMP assays. A second group of studies also reported relationships between toxicities of test materials (both pure chemicals and environmental samples) generated through the SMP assays and other species but relied on data generated within their own laboratories rather than from published literature values. This approach tends to be more reliable since each investigator has control over test variables associated with each assay conducted within their lab. Data drawn from multiple published studies containing data generated by a variety of individuals is inherently more variable due to inconsistencies in test protocols and investigator techniques from one laboratory to another. Miana et al. (14) compared the toxicity of tributyltin to the green alga Selenastrum capricornutum and the Cladoceran Daphnia magna to submitochondrial particles and concluded that SMP assay was fast, reproducible, and easily handled. Bettermann et al. (15) assessed the toxicity of elutriate samples from sediments previously demonstrated to be toxic to the amphipod Hyalella azteca. They reported a significant correlation between ETr EC50 values and amphipod survival for two of three watershed sites. No such relationship was observed between results from the RET assay and sediment elutriates from any of the watersheds. Dutka et al. (16) used a multispecies test battery to assess water and sediment toxicity from two river basins in Chile. The SMP RET assay was among those suggestive of toxicity in several of the samples collected during this study. Weideborg et al. (17) compared the RET variant with six other routine toxicity tests to assess the toxicity of 82 soluble and non-water-soluble chemicals. They reported similar EC50 values for both the RET variant and Microtox tests for low toxicity chemicals, with Microtox being the more sensitive of the two. However, the relationships

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among all of the tests for a diverse set of test substances was variable and may have been a function of test design rather than test sensitivity. Sherry et al. (18) assessed the toxicity of refinery effluents with Microtox, a variety of algae, invertebrate, and fish tests, and the RET variant of the SMP assay. They reported that acute toxicity was detected only by the Microtox and SMP tests. Argese et al. (19) compared the RET assay with Microtox for their sensitivity to 14 organotin compounds. They reported good agreement between the two assays with comparable sensitivity for organotins with an R2 of 0.92. Sheesley et al. (20) used the RET variant, the invertebrate Ceriodaphnia dubia, and the green alga S. capricornutum to assess the toxicity of aqueous and organic solvent extracts of atmospheric particulate matter from the Lake Michigan airshed. Based on a direct comparison of LC50 and EC50 values, the RET SMP assay was the most sensitive of the three for aqueous extracts of particulate matter from three different sites. ENVIRONMENTAL MONITORING WITH SMPs As outlined above, studies assessing the potential for SMPs as a routine biomonitor generally attempted to compare the sensitivity of one or more of the SMP assay variants with that of an established assay. Investigators either ranked assays by comparing each assay’s sensitivity to an individual chemical or environmental sample or generated regression analyses for pairs of assays over a range of toxicities from groups of test substances. However, while sensitivity should be a factor in the selection of surrogate assays, it is not the only parameter that needs to be considered. Biological monitoring, as taken in the current context, was instituted for protection of natural aquatic systems, not wildlife or human health protection. To that end, the initial species selected for that task were considered representative of the aquatic environment. Consequently, the most appropriate surrogate species or assay for that purpose would be one that is equally, but not overly, sensitive to a broad range of chemicals as the primary biomonitoring species while incorporating advantages not provided by the primary species. Such advantages might include reduced test duration time or reduced expense associated with the conductance of those tests. Adopting a surrogate assay that exhibits increased sensitivity relative to the primary test species may prompt expensive remedial actions that are not necessary for the protection of the system under study. SMP assays have exhibited the potential to be among the most sensitive assays conducted with a group of chemicals or environmental samples. One of the confounding issues related to sensitivity rankings is the change in rank among assays for different types of contaminants. The SMP assay variants are not immune to this type of variability as demonstrated by some of the studies cited above. The solution to this dilemma involves the development of multispecies test batteries with the components of those batteries exhibiting alternating sensitivities to varying chemical classes. Positive (toxic) responses by one or more components within the test battery should then be taken as an

indication of contamination. SMP assays have exhibited the potential for being a constructive component of a multispecies or multiassay test battery. As noted above, any assay adopted for biomonitoring purposes needs to be standardized so that results from different groups of investigators are compatible and comparable. In this regard, the SMP assays are only in a rudimentary stage of development. Manual test protocols only include an approach for generating EC50 values involving serial dilution of test solutions. There are no formalized screening procedures for whole environmental samples or order-of-magnitude dilutions for chemical samples. Additionally, the data analysis approach currently in use involves a subjective selection of data points used in the generation of an EC50 . This aspect of the assay will need to be evaluated so as to minimize differences in the test endpoints not necessarily related to the toxicity of the test material itself. Included within the standardization process is the reproducibility of an assay. There have been no studies addressing between-laboratory reproducibility for either of the SMP assay variants. The only published study related to this point focused on the within-laboratory repeatability of the ETr and RET assay variants (21). They reported coefficients-of-variation that were comparable to more traditional assays using three different reference toxicants. Since the level of variability exhibited by an assay increases in between-laboratory round robin studies in comparison with in-laboratory results, such a study is necessary to further consider SMP assays as surrogates for traditional aquatic toxicity tests. Lastly, SMPs are a manufactured test system in contrast with existing traditional assays that use whole organisms. A great deal of research has been invested in developing culture methods for standard test species so that tests are conducted with consistently healthy test organisms. There are no published studies available assessing variabilities associated with the manufacturing process aside from a preliminary study conducted within the author’s laboratory. CONCLUSION The SMP assay variants have exhibited the potential to serve as surrogate biomonitoring assays in freshwater systems. Test results have demonstrated that the one or both variants are as sensitive or more sensitive than traditional assays. However, SMP assays are only in a rudimentary stage of development with respect to biomonitoring applications. Both the manufacturing and testing protocols need to be standardized and evaluated prior to serious consideration of SMP assays as a legitimate surrogate biomonitoring option. BIBLIOGRAPHY 1. Weber, C.I. (1991). Methods for Measuring the Acute Toxicity of Effluents and Receiving Waters to Freshwater and Marine Organisms, 4th Edn. Environmental Monitoring Systems Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH, EPA/600/4-90/027.

MICROSCALE TEST RELATIONSHIPS TO RESPONSES TO TOXICANTS IN NATURAL SYSTEMS 2. Lewis, P.A., Klemm, D.J., Lazorchak, J.M., NordbergKing, T.J., Peltier, W.H., and Heber, M.A. (1994). Short-Term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms, 3rd Edn. Environmental Monitoring Systems Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH, EPA/600/4-91/002. 3. Blondin, G.A., Knobeloch, L.M., Read, H.W., and Harkin, J.M. (1987). Mammalian mitochondria as in vitro monitors of water quality. Bull. Environ. Contam. Toxicol. 38: 467–474. 4. Blondin, G.A., Knobeloch, L.M., Read, H.W., and Harkin, J.M. (1989). An in vitro submitochondrial bioassay for predicting acute toxicity in fish. In: Aquatic Toxicology and Environmental Fate: Eleventh Volume, ASTM STP 1007. G.W. Suter, II and M.A. Lewis (Eds.). American Society for Testing and Materials, Philadelphia, pp. 551–563. 5. Knobeloch, L.M., Blondin, G.A., Lyford, S.B., and Harkin, J.M. (1990). A rapid bioassay for chemicals that induce prooxidant states. J. Appl. Toxicol. 10: 1–5. 6. Knobeloch, L.M., Blondin, G.A., Read, H.W., and Harkin, J.M. (1990). Assessment of chemical toxicity using mammalian mitochondrial electron transport particles. Arch. Environ. Contam. Toxicol. 19: 828–835. 7. Hansen, M. and Smith, A.L. (1964). Studies on the mechanism of oxidative phosphorylation. VII. Preparation of a submitochondrial (ETPH ), which is capable of fully, coupled oxidative phosphorylation. Biochim. Biophys. Acta 81: 214–222. 8. Bragadin, M. and Dell’Antone, P. (1994). A new in vitro toxicity test based on the response to toxic substances in solutions of mitochondria from beef heart. Arch. Environ. Contam. Toxicol. 27: 410–414. 9. Argese, E. et al. (1994). Submitochondrial particle response to linear alkylbenzene sulfonates, nonylphenol polyethoxylates and their biodegradation derivatives. Environ. Toxicol. Chem. 13: 737–742. 10. Argese, E. et al. (1995). Submitochondrial particles as toxicity biosensors of chlorophenols. Environ. Toxicol. Chem. 14: 363–368. 11. Argese, E. et al. (1996). Submitochondrial particles as in vitro biosensors of heavy metal toxicity. J. Aquat. Ecosys. Health 5: 125–134. 12. Argese, E. et al. (2001). Assessment of chloroaniline toxicity by the submitochondrial particle assay. Environ. Toxicol. Chem. 20: 826–832. 13. Read, H.W., Harkin, J.M., and Gustavson, K.E. (1998). Environmental applications with submitochondrial particles. In: Microscale Testing in Aquatic Toxicology. P.G. Wells, K. Lee, and C. Blaise (Eds.). CRC Press, Boca Raton, FL, pp. 31–52. 14. Miana, P., Scotto, S., Perin, G., and Argese, E. (1993). Sensitivity of Selenastrum capricornutum, Daphnia magna and submitochondrial particles to tributyltin. Environ. Technol. 14: 175–181. 15. Bettermann, A.D., Lazorchak, J.M., and Dorofi, J.C. (1996). Profile of toxic response to sediments using whole-animal and in vitro submitochondrial particle (SMP) assays. Environ. Toxicol. Chem. 15: 319–324. 16. Dutka, B.J. et al. (1996). Water and sediment ecotoxicity studies in Temuco and Rapel River Basin, Chile. Environ. Toxicol. Water Qual. 11: 237–247. 17. Weideborg, M., Arctander Vik, E., Daae φfjord, G., and Kjφnnφ, O. (1997). Comparison of three marine screening tests and four Oslo and Paris Commission procedures to evaluate toxicity of offshore chemicals. Environ. Toxicol. Chem. 16: 384–389.

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18. Sherry, J., Scott, B., and Dutka, B. (1997). Use of various acute, sublethal and early life-stage tests to evaluate the toxicity of refinery effluents. Environ. Toxicol. Chem. 16: 2249–2257. 19. Argese, E. et al. (1998). Comparison of in vitro submitochondrial particle and Microtox assays for determining the toxicity of organotin compounds. Environ. Toxicol. Chem. 17: 1005–1012. 20. Sheesley, R.J. et al. (2004). Toxicity of ambient atmospheric particulate matter from the Lake Michigan (USA) airshed to aquatic organisms. Environ. Toxicol. Chem. 23: 133–140. 21. Doherty, F.G. and Gustavson, K.E. (2002). Repeatability of the submitochondrial particle assay. Ecotox. Environ. Safety 53: 122–128.

MICROSCALE TEST RELATIONSHIPS TO RESPONSES TO TOXICANTS IN NATURAL SYSTEMS JOHN CAIRNS, JR. Virginia Polytechnic Institute and State University Blacksburg, Virginia

A primary purpose of ecotoxicology is to estimate toxicity thresholds below which no observable deleterious effects can be detected upon ecosystems. Since uncertainty is unacceptably high when extrapolations are made from single species (1), tests at higher levels of biological organization are much more effective (2). Moreover, such levels of testing permit increased opportunities of testing for alteration of functional attributes (3). Large-scale tests are both risky and expensive; consequently, microscale testing has been developed. Microscale testing can be carried out with standardized communities, which are superb in furnishing a validated set of results. However, standardized communities do not closely resemble communities from natural systems. Communities from any two natural systems rarely contain the same species. However, any naturally derived community will contain species that span a range of tolerance to stress. This range of tolerance can be generalized from one natural community to another. This extrapolation provides predictive capabilities, which are the ultimate goal of ecotoxicological testing. Furthermore, culturing test organisms for use in microscale testing customarily consumes as much or more time than the testing itself. Microscale toxicity testing with communities obtained from natural systems has many benefits, in addition to reducing culture problems typical of laboratory-assembled communities. Methods are even available for carrying out microscale toxicity testing in natural systems (4). Communities of organisms that have colonized artificial substrates can be collected. These collections are not artificial communities, although convenience sometimes dictates naming these communities ‘‘artificial’’ in order to distinguish them from collections made directly from natural substrates. Artificial substrates (5) have major advantages in microscale testing.

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1. The age of the community is known. 2. A determination can be made of when the community has reached a dynamic equilibrium comparable to that of the system that furnished the colonizing organisms. 3. Natural systems are not disturbed by sampling efforts. 4. Communities can be moved to the microscale test system with minimal disturbance to the community that is the subject of the test. 5. Communities in the natural system can be monitored to determine if changes in either structure or function have occurred that were evident in the microscale system as a result of toxic stress. 6. Since microbial species have a cosmopolitan distribution, results from different geographic regions can be compared. 7. Since microorganisms and macroinvertebrates are much more abundant than larger organisms higher in the food chain, their use in toxicity testing is more likely to be accepted by animal rights groups. 8. Microscale tests allow a setup of many more concentrations in the same space that would be necessary for far fewer larger scale tests. 9. Automation is possible for the counting of numbers of individuals per species and total number of some species used in microscale toxicity tests (6). Microscale testing units are not miniature ecosystems. Properly designed, they can mimic selected cause–effect pathways (e.g., nutrient cycling and prey relationships) (7) not observable at lower levels of biological complexity. However, they do not have all the cause–effect pathways found in natural ecosystems and landscapes. Some relevant discussions of complex system testing (8) and examples of microscale testing (9,10) are available in the literature. Suitability of the microscale test design can be confirmed by comparing measurements made in it to similar measurements in natural systems (11). Methods are available for the statistical analysis of this unique evidence (12–14). One of the most difficult attributes to include in microscale testing is the invasive pressure of organisms that are attempting to colonize (12). This invasion pressure is one of the major factors in succession of species in natural systems. The major disadvantage to microscale toxicity testing is that sometimes a modest degree of taxonomic ability is essential. Taxonomy is often not taught in many American institutions of higher learning. However, staff members with no taxonomic ability can be instructed in just a few months in levels of identification necessary in some microscale tests, although years of experience are necessary for the more complex microscale toxicity tests. BIBLIOGRAPHY 1. Cairns, J. Jr. (1983). Are single species toxicity tests alone adequate for estimating environmental hazard? Hydrobiologia 100: 47–57.

2. Cairns, J. Jr. (Ed.) (1986). Community Toxicity Testing, STP920. American Society for Testing and Materials, Philadelphia. 3. Cairns, J. Jr. and Pratt, J.R. (Eds.) (1989). Functional Testing of Aquatic Biota for Estimating Hazards of Chemicals, STP988. American Society for Testing and Materials, Philadelphia. 4. Arnegard, M.E., McCormick, P.V., and Cairns, J. Jr. (1998). Effects of copper on periphyton communities assessed in situusing chemical-diffusing substrates. Hydrobiologia 385: 163–170. 5. Cairns, J. Jr. (1982). Artificial Substrates. Ann Arbor Science Publishers, Ann Arbor, MI. 6. Cairns, J. Jr. and Niederlehner, B.R. (Eds.) (1995). Ecological Toxicity Testing: Scale, Complexity and Relevance. Lewis Publishers, Chelsea, MI. 7. Clements, W.H., Cherry, D.S., and Cairns, J. Jr. (1989). The influence of copper exposure on predator–prey interactions in aquatic insect communities. Freshwater Biol. 21: 483–488. 8. Hoffman, D.J., Rattner, B.A., Burton, G.A. Jr., and Cairns, J. Jr. (2003). Handbook of Ecotoxicology, 2nd Edn. Lewis Publishers/CRC Press, Boca Raton, FL. 9. McCormick, P.V., Belanger, S.E., and Cairns, J. Jr. (1997). Evaluating the hazard of dodecyl alkyl sulphate to natural ecosystems using indigenous protistan communities. Ecotoxicology 6: 67–85. 10. Orvos, D.R., Scanferlato, V.S., Lacy, G.H., and Cairns, J. Jr. (1989). Fate and effects of genetically-engineered Erwinia carotovora in terrestrial and aquatic microcosms. 89th Annual Meeting of the American Society for Microbiology, New Orleans, Louisiana, p. 355. 11. Niederlehner, B.R. and Cairns, J. Jr. (1994). Consistency and sensitivity of community level endpoints in microcosm tests. J. Aquat. Ecosys. Health 3: 93–99. 12. Pontasch, K.W. and Cairns, J. Jr. (1989). Establishing and maintaining laboratory-based microcosms of riffle insect communities: their potential for multispecies toxicity tests. Hydrobiologia 175: 49–60. 13. Pontasch, K.W., Smith, E.P., and Cairns, J. Jr. (1989). Diversity indices, community comparison indices and canonical discriminant analysis: interpreting the results of multispecies toxicity tests. Water Res. 23: 1229–1238. 14. Smith, E.P. and Cairns, J. Jr. (1993). Extrapolation methods for setting ecological standards for water quality: statistical and ecological concerns. Ecotoxicology 2: 203–219.

TOXICITY IDENTIFICATION EVALUATION PHILIP J. MARKLE Whittier, California

Bioassays for aquatic chronic and acute toxicity testing using standardized methods have been used to measure toxic effects and in some cases can even estimate the magnitude of toxicity for many years. Their use has been incorporated into regulatory requirements for point and nonpoint discharges to both marine and freshwater environments. However, these standard methods provide virtually no information on which constituent(s) are responsible for the observed effect. Reliance on only chemical-specific analyses to determine the causative

TOXICITY IDENTIFICATION EVALUATION

agent(s) in a water sample exhibiting toxicity or suspected of being toxic to aquatic organisms can be misleading. Initially, the list of potential toxicants that would need to be quantified is nearly limitless, not to mention costly. Additionally, even GC/MS analyses may not be sensitive enough to detect low concentrations of some toxic substances. Furthermore, even if elevated levels of a particular compound are identified, the compound may or may not be bioavailable, and receiving water characteristics (i.e., total organic carbon, hardness, salinity, pH) may confound the observed toxicological sensitivity. Chemical quantification will also not identify any additive, synergistic, or antagonistic properties of many toxicant combinations. It was specifically because of these concerns that aquatic toxicity testing was developed and incorporated into many water pollution control plans. The U.S. EPA has developed and published several manuals detailing specific methods for identifying toxic constituents (1–4). These methods are collectively referred to as ‘‘toxicity identification evaluations’’ (TIEs) and are often incorporated as part of a larger site-specific study identified as a ‘‘toxicity reduction evaluation’’ (TRE). The ultimate goal of a TRE is to identify toxic constituents, identify their sources, evaluate toxicity control options, and eventually eliminate the toxicity. The TIE is typically used to identify the toxic constituents and to evaluate the effectiveness of the toxicity control mechanisms. During the initial stages of a TIE (phase 1), toxicity is characterized through a series of sample manipulations followed by toxicity testing. These manipulations typically include pH adjustments, chemical additions (EDTA and sodium thiosulfate), chemical extractions (solid phase extraction), and physical manipulations, (filtration and aeration) followed by toxicity testing to assess any increases or decreases resulting from the manipulation. The relative increases or decreases in observed toxicity in the subsequent toxicity tests conducted on the manipulated sample often characterize the properties of the chemical constituent(s). For example, a decrease in toxicity observed in the EDTA addition tests would indicate possible metal toxicity. A list of commonly applied phase 1 TIE manipulations and their interpretation is contained in Table 1. Other manipulations and result interpretations are specifically detailed in the U.S. EPA manuals. Once characterized in phase 1, the investigator would proceed to phase 2 to identify the individual constituent(s). The phase 2 TIE procedures incorporate additional toxicity testing and/or analytical methods. The testing and/or analytical measurements vary, depending on the phase 1 characterization interpretations. The last phase of the TIE procedure (phase 3) consists of a series of final confirmation steps designed to provide a ‘‘weight of evidence’’ approach in confirming the causative agent(s). Through the establishment of causal links and correlations, the approach is designed to ensure that suspected toxicants are conclusively identified and consistent from sample to sample. Identification of what is ‘‘toxic’’ in aquatic toxicity tests is most often determined quantitatively through the regulatory process as permit limits or objectives and no definitive standards have been defined or are

381

Table 1. Summary of Commonly Applied Phase 1 TIE Manipulations and Associated Interpretation TIE Manipulation

Purpose/Interpretation

Baseline—no manipulation EDTA addition Sodium thiosulfate addition Piperonyl butoxide addition

Conducted to determine if toxicity is present Controls most metal (cationic) toxicity Reduces easily oxidizable compounds such as chlorine or some metals Controls toxicity due to organophosphate pesticides An increase in toxicity would indicate possible pyrethroid pesticide toxicity Controls ammonia/metal toxicity A decrease in toxicity may indicate ammonia/metal toxicity Controls some metal toxicity An increase in toxicity would indicate ammonia and/or some metal toxicity Removes volatile compounds and some surfactants Removes solids and some surfactants Removes nonpolar organic compounds and some surfactants Recovery of toxicity from the SPE column indicates nonpolar organic toxicity Failure to recover toxicity from the SPE column indicates surfactant toxicity

pH control at 6.5

pH control at 8.5

Aeration Filtration Solid phase extraction (SPE)

universally used. Although no universal definitions exist, several measures of toxicity are more commonly employed and seem to have achieved greater acceptance. These include the use of the ‘‘no observed effect concentration’’ (NOEC) or ‘‘no observed effect level’’ (NOEL). The NOEC and NOEL use hypothesis testing to identify statistically significant differences relative to a nontoxic control. The NOEC or NOEL is defined as the highest concentration not significantly different from the control. Another commonly used analysis involves various point estimation techniques. These quantitative analyses use dose–response data to estimate ‘‘safe’’ or ‘‘nontoxic’’ concentrations or effects using metrics such as the LC50 (lethal concentration causing a 50% effect) or EC/IC25 (effective or inhibition concentration causing a 25% effect). Due to the large amount of toxicity testing required in the TIE process, reductions in testing replication and exposure volume and duration are often made to save on sample and staffing resources. Results are typically represented qualitatively as opposed to quantitatively that is, relative increases or decreases in toxicity compared to the no manipulation treatment or appropriately manipulated control were observed. Although fairly straightforward, several things can significantly complicate the TIE process. To identify the causative agent, a sample must first exhibit toxicity. For this reason, the persistence of toxicity is often a confounding factor. Multiple samples eventually need to be collected and tested during the course of the analysis. If toxicity is episodic or sporadic, collection and subsequent testing of a suitably toxic sample will also be more unlikely. Most TIEs are conducted during

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WHOLE EFFLUENT TOXICITY CONTROLS

the course of 1 to 2 weeks requiring extended holding of samples. Constituents that rapidly degrade during this extended holding time can often confound identification due to a loss of toxicity. Furthermore, the numerous manipulations and increased holding time necessary in conducting a TIE may also alter basic water quality characteristics that may artificially affect the observed toxicity. For these reasons, successful completion of a TIE is much more likely in samples exhibiting a large amount of toxicity. Another common complication involves multiple constituents. If a sample contains two or more toxic constituents, the investigator will need to identify at least one of the constituents and selectively remove or control its toxicity without impacting the others prior to attempting to identify the other constituent(s). Although much more work conducted using freshwater organisms has resulted in greater acceptance and standardization in the freshwater methods, the described TIE procedures have been successfully used to identify and ultimately control toxic compounds in effluents and freshwater and marine receiving waters. It would be impractical to detail all of the possible TIE manipulations and their interpretation in this overview. The referenced manuals provide specific details on all aspects of the conduct and interpretation of TIE results. Copies of the referenced manuals may be obtained directly from the U.S. EPA (http://www.epa.gov/waterscience/WET/). BIBLIOGRAPHY 1. EPA/600/6-91/005F. (1992). Toxicity Identification: Characterization of Chronically Toxic Effluents, Phase 1. U.S. EPA Office of Research and Development, Washington, DC. 2. EPA/600/6-91/003. (1991). Methods for Aquatic Toxicity Identification Evaluations-Phase 1 Toxicity Characterization Procedures, 2nd Edn. U.S. EPA Office of Research and Development, Washington, DC. 3. EPA/600R-92/080. (1993). Methods for Aquatic Toxicity Identification Evaluations-Phase 2 Toxicity Identification Procedures for Samples Exhibiting Acute and Chronic Toxicity. U.S. EPA Office of Research and Development, Washington, DC. 4. EPA/600/3-88/036. (1989). Methods for Aquatic Toxicity Identification Evaluations-Phase III Toxicity Confirmation Procedures. U.S. EPA Environmental Research Laboratory, Duluth, MN.

WHOLE EFFLUENT TOXICITY CONTROLS PHILIP J. MARKLE Whittier, California

The selection of an appropriate control sample/water for whole effluent toxicity testing is a critical experimental design component. Whole effluent toxicity (WET) testing has been an important tool for toxicity compliance and research testing alike to identify acute and chronic toxicity in effluents and receiving waters. The U.S. EPA and others have developed several manuals detailing specific WET methods; many have been incorporated

into the National Pollutant Discharge Elimination System (NPDES) permit program for compliance determination. The primary objective of these aquatic toxicity tests is to estimate a maximum ‘‘safe’’ concentration of toxic substances in a discharge or receiving water that will allow for normal growth and propagation of aquatic organisms. A typical WET test experimental design consists of exposing organisms under controlled laboratory conditions to a series of effluent, receiving water, and/or toxicant dosed samples and recording biological observations such as reproduction, growth, and survival. A set of exposures is concurrently conducted using control water. The biological results obtained from the effluent/receiving water exposures are then qualitatively or quantitatively compared to the results obtained in the control water exposure to identify relative reductions in biological response as an indication of toxicity. Effects relative to the control are used to estimate toxicity in a WET test, so control water selection can be critical. Control water that stimulates an unusually large response or enhancement when compared to a more normal response in the effluent/receiving water is more likely to identify falsely that a sample is ‘‘toxic,’’ when it was not. Likewise, control water that exhibits a suppressed response when compared to an effluent/receiving water that exhibits toxicity is more likely to be identified as nontoxic when in fact it was toxic. Nontoxicity related factors associated with control waters can elicit a stimulatory or inhibitory response in test organisms. These factors need to be identified by the investigator and carefully controlled to minimize any misidentification of toxicity or nontoxicity in a WET test. In multiconcentration tests, the same control water is also used to dilute the effluent or receiving water to the appropriate concentration. For this reason, control water is often referred to as dilution water. Although the amount of sample increases as concentration increases, the amount of dilution water likewise decreases as concentration increases. The U.S.EPA whole effluent toxicity testing protocols define acceptable dilution water as water that is appropriate for the test objectives, supports adequate test organism response measured in the test, is consistent in quality, and is free of contaminants that could cause toxicity (1–3). Although test organisms may have a wide range of tolerance to many commonly measured water characteristics (pH, hardness, conductivity, salinity, etc.), it is likely that the organisms have a much narrower ‘‘optimal’’ range. Differences in these basic water characteristics between control water and effluent samples may account for an apparent observed difference in toxicological response in a WET test when in reality, the sample was actually nontoxic. Furthermore, control water/effluent sample interactions in multiple concentration tests could increase or decrease apparent toxicity and result in improper identification of toxicity. Selection of an appropriate control water will depend in some part on the objectives of the experiment. If the primary objective of the test is to quantify the relative toxicity of a sample over time or location (i.e., is sample ‘‘A’’ more or less toxic than sample

DEVELOPMENT AND APPLICATION OF SEDIMENT TOXICITY TESTS FOR REGULATORY PURPOSES

‘‘B,’’ or is discharge ‘‘A’’ more toxic this month than it was last month), synthetic control water would be most appropriate. Dilution water characteristics such as hardness, pH, magnesium/calcium ratios, and many others can drastically effect the toxicological response in a test. It is impossible to understand or predict all of the dilution water/sample interactions that may effect the toxicological response, so the incorporation of standard synthetic control water allows the investigator to eliminate these concerns when the objective of toxicity testing is to measure relative toxicity. Synthetic dilution water is prepared by dissolving fixed amounts of reagent grade salts into high purity de-ionized water. For synthetic freshwater, NaHCO3 , CaSO4 , MgSO4 , and KCl are the most commonly incorporated reagent salts. Commercially available seawater reagents are available for testing with estuarine and marine species. The referenced U.S. EPA method protocols provide detailed preparatory procedures for many of these waters. The advantages of synthetic waters are that they are very consistent from batch to batch, would not be expected to contain toxic constituents, and are easily prepared. The disadvantages of synthetic waters are that they are typically nutrient poor and although adequate, may not be ‘‘optimal’’ water for the test organisms. If the objective of the test is to estimate or predict ecological impacts on the receiving water, control water with similar receiving water characteristics should be used. The more similar the control water characteristics are to the receiving water, the more predictive the toxicity test will be. Characteristics most commonly simulated include pH, hardness, alkalinity, and conductivity. However, differences between receiving water and control water in other less understood characteristics such as total organic carbon and micronutrient concentration, to name only a few, may significantly compromise the predictive ability of the toxicity test and may require further investigation. An immediate upstream receiving water not influenced by the discharge may be a suitable source. The advantages to using receiving water is that sample/control water interactions are accounted for in the toxicity test design with little effort and surface waters tend to be higher in micronutrient content than synthetic waters. Disadvantages of using receiving water include the possibility that they may contain toxic constituents, they may contain pathogens or predatory organisms, water quality characteristics are not typically consistent over time, and upstream receiving water may not be available. Additionally, any manipulations of a sample prior to or during a toxicity test should also be incorporated into the control/dilution water. For instance, if a sample requires aeration to maintain appropriate dissolved oxygen levels, the control should be similarly aerated to compensate for any ‘‘artifactual’’ increase or decrease in toxicological response that may occur from the manipulation. This becomes increasingly more important when conducting toxicity identification evaluations (TIEs). In a TIE, toxic effluent or receiving waters are manipulated to isolate or remove specific compounds or classes of compounds. Many of these manipulations involve chemical extractions and/or the addition of substances that could affect the response.

383

Appropriately manipulated control water aliquots must also be tested and compared to identify any potentially stimulatory or inhibitory effects. BIBLIOGRAPHY 1. U.S. Environmental Protection Agency. (2002). Short-term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms, 4th Edn. EPA/821/R-02/013. Office of Water, Washington, DC. 2. U.S. Environmental Protection Agency. (2002). Short-Term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Marine and Estuarine Organisms. 3rd Edn. EPA/821/R-02/014. Office of Water, Washington, DC. 3. U.S. Environmental Protection Agency. (2002). Methods for Measuring the Acute Toxicity of Effluents and Receiving Waters to Freshwater and Marine Organisms, 5th Edn. EPA/821/R02/012. Office of Water, Washington, DC.

DEVELOPMENT AND APPLICATION OF SEDIMENT TOXICITY TESTS FOR REGULATORY PURPOSES M.G.J HARTL F.N.A.M. VAN PELT J. O’HALLORAN Environmental Research Institute University College Cork, Ireland

INTRODUCTION Traditional approaches to sediment toxicity assessment have employed chemical analysis to identify and quantify pollutants present. This approach, however, will only provide information on chemical classes that are analyzed and, when used alone, is of little value in ecotoxicological assessment, because toxicity cannot be determined on the basis of chemistry alone (1). Toxicity is ultimately defined as a measurable biological response to a particular substance or mixture of substances (2,3). Toxicity testing provides a more direct means of assessing the potential adverse effects of contaminants. In a complementary way, ecotoxicological assessment should provide a measure of the combined effects of the compounds in a complex sample, thereby taking into account any additive, antagonistic, or synergistic effects and include a degree of biological relevance. An ecotoxicological sediment assessment necessitates a tiered approach using different endpoints and several test species representing different trophic levels, because the effect of pollutants may differ between species. Thus, a battery of bioassays rather than single species assays should be employed. Battery style approaches in the evaluation of sediment toxicity (both freshwater and marine) have been described (2,4–8). For example, the SED-TOX Index recommends the integration of multitrophic and multiexposure route tests (different

384

DEVELOPMENT AND APPLICATION OF SEDIMENT TOXICITY TESTS FOR REGULATORY PURPOSES

sediment phases) in toxicity assessment of sediments (8). The ecotoxicological triad explores a similar concept (9). In this article, we define sediments, consider their ecotoxicological significance, and summarize some of the key sediment toxicity test systems in use and/or development.

interface, pore water, and elutriates. Examination of any single sediment phase may be insufficient to give an accurate ecotoxicological assessment (23,24). Recent investigations using field-collected sediment samples have demonstrated that the whole sediment phase can be used in toxicity assessment under controlled laboratory conditions (see Tables 1–4).

WHAT ARE AQUATIC SEDIMENTS? Sediments represent an open, dynamic, and heterogeneous biogeochemical system (10) that is formed by an accumulation of particulate matter derived from continental runoff, coastal erosion, or atmospheric deposition, which precipitates to the bottom of a water body. Typically, sediments are an accumulation of particulate mineral matter, inorganic matter of biogenic origin, organic matter in various stages of synthesis or decomposition, and water (11,12). Sediments normally consist of an inorganic matrix coated with organic matter (13), giving rise to a wide variety of physical, chemical, and biological characteristics. Control sediments can be formulated from particulate matter of known origin and characteristics for use in toxicity testing (12,14,15). The ecotoxicological significance lies in the tendency of many pollutants, especially the less polar organic contaminants and trace elements, to show a strong affinity to suspended particulate matter (16,17). They are sequestered from the water column and incorporated into the sediment. Redox conditions influence the chemical speciation, sorption behavior, and partition coefficients of incorporated compounds and trace elements. Undisturbed sediments tend to accumulate many chemical compounds, and so act as sinks. The retention capacity of sediments for many pollutants is dependent on salinity, pH, Eh , and/or mechanical disturbance. Changes in these conditions can result in release of the contaminants, and therefore sediments may act not only as sinks but also as secondary sources, directing often highly concentrated pulses of pollutants at benthic organisms (i.e., organisms intimately associated with sediments). Fine-grained, organically rich sediments play a major role in the biogeochemical fate of chemicals, both of natural and anthropogenic origin, and, along with water quality, have increasingly become the focus of attention in assessing the state of the aquatic environment. In situ sediment toxicity assessments are rarely performed because of logistics, the difficulties of identifying reference and control sites, and controlling or correcting for confounding environmental variables. Thus field-collected sediment samples are used in laboratory-based toxicity test models. Sediments vary on both a spatial and temporal scale and are structured systems of oxic and anoxic zones (18). These two zones display very different chemical conditions (19,20). Accordingly, during the collection of sediment samples, one must ensure that these zones are not mixed, as this may result in differences in redox status, which will affect the bioavailability of contaminants. The oxic layer of the sediment is preferably sampled and used for toxicity testing especially because this layer interfaces with the water column in situ (21,22). Sediments are not homogeneous but are composed of the following phases: whole sediment, sediment–water

TEST SYSTEMS A comprehensive assessment of potential sediment toxicity requires the consideration of multiple exposure phases and multiple test models representing different trophic levels and sediment related habitats. Primary criteria for test species selection for assessing sediment contamination and toxicity include the species’ ecological and/or economical importance and its relative sensitivity to sediment contamination, predictable and consistent response of control organisms, ease of culture and maintenance, short duration, replicable, relatively inexpensive, comparable, and ecologically relevant (6,25,26). In addition to species selection, the endpoints in sediment toxicity tests depend on the question being addressed in the environmental risk assessment (2) and may include acute and long-term toxicity, endocrine, reproductive, and genotoxic effects. The majority of test systems in use for regulatory purposes are commercial test kits assessing acute general effects on microorganisms using sediment extracts (Table 1). Sediment pore water extracts (also known as interstitial water) are defined as the water occupying the space between sediment particles (27). Contaminants in pore water represent the water-soluble, bioavailable fraction and, as a result, may be a major route of exposure to infaunal species (28–30). The use of elutriate extracts, as opposed to pore water extracts, provides information on the leaching potential of sediment-associated contaminants and may therefore yield important data on the potential adverse effects to benthic organisms, following disturbance of the underlying sediment (6,31). Methods applicable to whole sediment, sediment suspension, sediment elutriate, pore-water extracts, and/or sediment extracts from the marine and freshwater environment have been previously reviewed (32). These test systems are well established, validated and reproducible, fast, cheap, and require little specialized training. In addition, in vitro models, using cells derived from a range of taxa, are currently being developed and validated (22). All these tests are suitable for screening purposes and initial hazard identification. However, they have limited ecological relevance because they are often restricted to nonspecific endpoints or a single trophic level. Therefore, the use and development of a multiple test system or test battery, using various endpoints for both general toxicity (see Tables 1 and 2) and specific toxicities (e.g., genotoxic and reproductive effects; see Tables 3 and 4) in sediment-associated organisms from several taxa representing different trophic levels, is desirable. These models may have a higher ecological relevance than the microbial test systems. In some cases, multiple endpoints for different toxic effects (acute, long term, and specific)

DEVELOPMENT AND APPLICATION OF SEDIMENT TOXICITY TESTS FOR REGULATORY PURPOSES

385

Table 1. Examples of Test Systems Used for Sediment Toxicity Assessment—Acute Toxicity Tests Test Phase Endpoint Enzyme inhibition/ bioluminescence

Behavior Motility

Taxa

Chemicals Identifieda

Bacteria Microtox ToxiChromoPad LUMIStox BioTox MetPAD Toxi-Chromotest

PAHs, POPs, metals PAHs, POPs unspecified Pesticides Metals PAHs, POPs

FW diatom Invertebrates (Daphtoxkit )

Reburial a b

In vivo

In vitro

Sediment

Extractsb

+ + +

+ + +

p,e

+ +

+

e p,e,o e e

+

e

+ Pesticides Resin-acid

p,e,o

+ +

+

Reference

6,34–38 38 39 3,40 41 6,38 42 3,40 43

Major chemical classes identified in the sediments. p: porewater extracts; e: elutriates; o: organic solvent extracts; PAHs: polycyclic aromatic hydrocarbons; POPs: persistent organic pollutants.

Table 2. Examples of Test Systems Used for Sediment Toxicity Assessment—Subchronic Toxicity Tests Test Phase Endpoint

Taxa

Chemicals Identifieda

In vivo

PAHs, POPs, metals

+

PAHs, POPs, metals

+

In vitro

Sediment

Extractsb

+

e, p

Reference

Survival Invertebrates 32,44,45

Vertebrates e, o, p

32,46

Growth inhibition FW Algaltoxkit FW microalgae Marine microalgae

PAHs, PCBs PAHs, PCBs

+ +

+ +

o

38 47 6

Organotins, metals

+

+

48–50

Metals

+

+

51,52

PAHs, PCBs

+

+

53

PAHs, OCPs, metals

+

+

Behavior Invertebrates Vertebrates Enzyme induction EROD

Invertebrates Vertebrates

a b

+

+

o

54–67

Major chemical classes identified in the sediments. p: porewater extracts; e: elutriates; o: organic solvent extracts; PAHs: polycyclic aromatic hydrocarbons; POPs: persistent organic pollutants.

or single endpoints in multiple organ systems have been used in the same test species in order to observe potential toxicity on various levels of biological organization (33). Unfortunately, this type of approach is currently not accepted for regulatory purposes, because many of the bioassays involved are generally less well validated. Therefore, we recommend that sediment toxicity assessments should be further developed and evaluated using a tiered approached, consisting of screening using short-term general toxicity tests (Tier 1); hazard identification applying more specific (multiple) endpoints in multiorganism experiments, representing different trophic levels and habitats associated with sediments, as well as different modes of bioavailability by using both sediment extracts and whole sediments (Tier 2); and in situ

ecosystem function, for example, lifetime reproductive success, and components of biodiversity (Tier 3). BIBLIOGRAPHY 1. Heida, H. and van der Oost, R. (1996). Water Sci. Technol. 34: 109–116. 2. Chapman, P.M. et al. (2002). Mar. Pollut. Bull. 44: 271– 278. 3. Fernandez-Alba, A.R., Guil, M.D.H., Lopez, G.D., and Chisti, Y. (2002). Anal. Chim. Acta 451: 195–202. 4. Dutka, B.J., Tuominen, T., Churchland, L., and Kwan, K.K. (1989). Hydrobiologia 188: 301–315. 5. Giesy, J.P. and Hoke, R.A.J. (1989). Gt. Lakes Res. 15: 539–569.

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DEVELOPMENT AND APPLICATION OF SEDIMENT TOXICITY TESTS FOR REGULATORY PURPOSES Table 3. Examples of Test Systems Used for Sediment Toxicity Assessment—Genotoxicity Tests Test Phase

Endpoint

Chemicals Identifieda

Taxa

In vivo

In vitro

Sediment

Extractsb

+ +

+

o p,e,o

Reference

Mutation Bacteria AMES test Mutatox

PAHs, POPs PAHs, POPs

68 69

Micronucleus Vertebrates PAHs, POPs

+

+

70

POPs PAHs, metals

+ +

+ +

71 33

PAHs, POPs

+

+

65,70–74

PAHs, PCBs

+

+

59,75

SSBs Invertebrates

Vertebrates DNA adducts Vertebrates a b

Major chemical classes identified in the sediments. p: porewater extracts; e: elutriates; o: organic solvent extracts; PAHs: polycyclic aromatic hydrocarbons; POPs: persistent organic pollutants.

Table 4. Examples of Test Systems Used for Sediment Toxicity Assessment—Endocrine and Reproduction Tests Test Phase Endpoint

Taxa

Chemicals Identifieda

In vivo

In vitro

Sediment

Extractsb

Reference

Invertebrates Imposex Larval development Spermiotoxicity Emergence

Organotins PAHs, metals PAHS, POPs Unspecified

+ +

PAHS, POPs PAHS, POPs Unspecified

+

+ e,o,p p

+ +

+

76 32,77 44,78 32

Vertebrates Estrogen-like activity Fertility Vitellogenin a b

o +

+

+ +

79 80 81,82

Major chemical classes identified in the sediments. p: porewater extracts; e: elutriates; o: organic solvent extracts; PAHs: polycyclic aromatic hydrocarbons; POPs: persistent organic pollutants.

6. Cheung, Y.H. et al. (1997). Arch. Environ. Contam. Toxicol. 32: 260–267.

15. Quevauviller, P. and Ariese, F. (2001). Trac-Trends. Anal. Chem. 20: 207–218.

7. Matthiessen, P. et al. (1998). Mar. Environ. Res. 45: 1–15.

16. IEEE. (1987). Organotin Symposium Oceans’86. Vol. 4. IEEE, Washington, DC, pp. 1370–1374.

8. Bombardier, M. and Bermingham, N. (1999). Environ. Toxicol. Chem. 18: 685–698. 9. Chapman, P.M. (2000). Int. J. Environ. Pollut. 13: 351. 10. Chapman, P., Bishay, F., Power, E., Hall, K., Harding, L., McLeay, D., Nassichuk, M., and Knapp, W. (Eds.). (1991). 17th Annual Aquatic Toxicology Workshop. In: Canadian Technological Report in Fisheries and Aquatic Science. Vol. 1. Vancouver, BC, pp 323–330. 11. Knezovich, J.P., Harrison, F.L., and Wilhelm, R.G. (1987). Water Air Soil Pollut. 32: 233. 12. ASTM. (1994). American Society for Testing and Materials: Terminology. ASTM, Provo, UT. 13. Rand, G.M., Wells, P.G., and McCarty, L.S. (1997). Fundamentals of Aquatic Toxicology—Effects, Environmenatl Fate and Risk Assessment, 2nd Edn. G.M. Rand (Ed.). Taylor and Francis, London, pp. 3–67. 14. Suedel, B.C. and Rodgers, J.H. (1994). Environ. Toxicol. Chem. 13: 1163.

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INTRODUCTION Algal toxins have various adverse implications on the ecosystem directly and indirectly. Cyanotoxins, a group of algal toxins produced by toxic cyanobacteria, are of

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great concern. The understanding of their occurrence, properties, detection, and removal from water bodies is of importance for monitoring and management of cyanotoxins in freshwater bodies. ECOLOGY OF TOXIC CYANOBACTERIA IN WATER Over 40 genera of cyanobacteria are toxic, and the toxic species with particular public health concern generally inhabit freshwater bodies. They are classified into three groups according to the toxin produced: hepatotoxinproducing species (e.g., Anabaena, Anabaenopsis, Microcystis, Nodularia, Oscillatoria, and Cylindrospermopsis); neurotoxin-producing species (e.g., Anabaena, Aphanizomenon, and Lyngbya); and dermatotoxin-producing species (e.g., Lyngbya; and Schizothrix) (1,2). The toxic cyanobacterial bloom usually occurs in the surface, near-shore area of slow-flowing freshwater bodies. The formation of cyanobacterial bloom and the associated occurrence of cyanotoxins are affected by a number of environmental parameters such as light intensity, temperature, nutrients, trace metals, and organic matters (3). The progressive eutrophication has been reported to be the major cause for the formation of cyanobacterial blooms (4). CYANOTOXINS AND RELATED HEALTH PROBLEMS Cyanotoxins are basically classified into three types according to their toxicological targets: hepatotoxins (e.g., microcystins, nodularins, cylindrospermopsins), neurotoxins (e.g., anatoxins, saxitoxins), and dermatotoxins (e.g., aplysiatoxin, lyngbyatoxin A) (5). Hepatotoxins The hepatotoxins mainly target the liver. The three major hepatotoxins are microcystins, nodularins, and cylindrospermopsins. Microcystins are the most implicated cyanotoxins in animal and human poisonings and can be produced by several genera, including Microcystis, Anabaena, Oscillatoria, Nostoc, and Anabaenopsis. Microcystins are cyclic peptides that are made up of five nonprotein amino acids and two protein amino acids (Fig. 1). The toxicity of microcystins is associated with the

presence of Adda (3-amino-9-methoxy-2,6,8- trimethyl-10phenyldeca-4,6-dienoic acid), which has a characteristic violet absorbance at 238 nm (6). Structural variants of microcystins differ in the presence of two protein amino acids (X and Z), two groups (R1 and R2), and two demethylated positions (3 and 7). The molecular weight of microcystins ranges from 800 to 1100 daltons (7). Microcystins can inhibit hepatocyte protein phosphatases 1 and 2A (8,9). The contamination of microcystins in drinking water is associated with a high incidence of primary liver cancer. The LD50 of the extreme toxic microcystin, microcystin-LR, is 50 µg kg−1 body weight in mice by intraperitoneal (i.p.) injection (10). Nodularins are cyclic pentapeptides and structurally similar to microcystins (Fig. 2). Until now, only four variants of nodularin have been identified in Nodularia spumigena. Nodularin can also inhibit the activities of protein phosphatases 1 and 2A and potently promote tumor formation (11,12). The LD50 of nodularin in mice is 30 µg kg−1 body weight by i.p. injection (10). In addition, long-term exposure to a low dose of nodularins or microcystins may cause progressive changes in liver tissue, leading to chronic inflammation and focal degeneration of hepatocytes (13). Cylindrospermopsins are tricyclic alkaloids (Fig. 3) and are produced by Cylindrospermopsis raciborskii, Aphanizomenon ovalisporum, Umezakia natans, and Raphidiopsis curvata. Cylindrospermopsins are potent inhibitors of protein synthesis and their main target organ is the liver. Unlike the other hepatotoxins, cylindrospermopsins can also affect other organs (e.g., kidney, thymus, and heart). The LD50 of cylindrospermopsin in mice is 2100 µg kg−1 body weight at 24 hours by i.p. injection (14). Neurotoxins The cyanobacterial neurotoxins are relatively unstable and less common when compared with hepatotoxins. They are, however, diverse in terms of the chemical structures and mammalian toxicities. The major neurotoxins are anatoxins and saxitoxins. Anatoxins are produced mainly by Anabaena species. The two common anatoxins are anatoxin-a and anatoxina(s) (Fig. 4). Anatoxin-a is a cholinergic agonist that binds to nicotinic acetylcholine receptors in nerves and neuromuscular junctions. Anatoxin-a(s) mainly inhibits acetylcholinesterase acitivity. The values of LD50 of anatoxin-a

7

6

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H3C Figure 1. General structure of microcystins [cycloD-Ala1 -X2 -D-methyl-isoaspartic acid (MeAsp)3 -Z4 Adda5 -D-isoglutamic acid (Glu)6 -N-methyldehydroalanine (Mdha)7 , R=H or CH3 ].

H

H H

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ALGAL TOXINS IN WATER

O H

OMe

N

N H NH

Me

H

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H Me H

Me

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389

NH

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Figure 2. Structure of nodularin.

Dermatotoxins

OH H

H

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Dermatotoxins are usually produced by benthic marine cyanobacteria (e.g., Lyngbya majuscule). Lyngbyatoxin A and aplysiatoxin are two specific dermatotoxins and are related to acute dermatitis and animal death. Long-term exposure to these toxins may lead to skin tumors (16).

O N

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Figure 3. Structure of cylindrospermopsin.

DETECTION OF CYANOTOXINS IN WATER (a)

(b) O N H

Me

Me

N N

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N O NH2

Me OH

P

O

O Figure 4. Structures of Anatoxin-a (a) and Anatoxin-a(s) (b).

O N2H R

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H

Figure 5. Structure of saxitoxin.

and anatoxin-a(s) are 200 µg kg−1 and 20 µg kg−1 body weight in mice by i.p. injection, respectively (15). Saxitoxins (Fig. 5), known as marine paralytic shellfish poisons (PSPs), are recently found in freshwater cyanobacteria including Anabaena circinalis, Lyngbya wollei, Cylindrospermopsis raciborskii, and Planktothrix sp. The toxicity of saxitoxins in mice is different depending on their variants. Saxitoxin is the most potent PSP with LD50 of 10 µg kg−1 body weight in mice by i.p. injection (5).

The general methods developed for detection of cyanotoxins include chemical analyses, for example, highperformance liquid chromatography (HPLC), mass spectroscopy (MS), and nuclear magnetic resonance (NMR); biological assays, for example, mouse, invertebrate, and bacterial bioassays; and biochemical assays, for example, protein phosphatase inhibition assay and immunoassay (ELISA). In chemical analyses, HPLC is widely used for the detection of most cyanotoxins (17). LC/MS is the best method for the detection of saxitoxins and its variants (18). To identify and differentiate the variants of microcystins, fast atom bombardment mass spectroscopy (FABMS) and FABMS/MS methods have been developed (19). Mouse bioassay is the only method for the detection of all types of cyanotoxins compared with other methods (17). In invertebrate bioassay, brine shrimp, mosquito, fruitfly, house fly, and locust are commonly used target organisms (20,21). The invertebrate bioassay, however, is limited in the detection of some specific cyanotoxins. For example, house fly and locust are only sensitive to saxitoxins, whereas brine shrimp can be used only for detection of microcystins. Bacterial bioassay is seldom used because of its weakness on the reflection of the correlation between the actual concentrations of known cyanotoxin and the responses of the testing bacterium (17). Protein phosphatase inhibition assay is the most sensitive biochemical method for the analysis of microcystins and nodularins. It uses 32 P-labeled glycogen phosphorylase and the colorimetric protein phosphatase inhibition assay. This assay has proved to be an efficient screening method for water samples because of its simple operation. The protein phosphatase inhibition assay is currently adopted for the analysis of microcystins in drinking water.

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The detection limits for microcystin-LR in raw and finished drinking water are 0.87 µg L−1 and 0.09 µg L−1 , respectively (22). The protein phosphatase inhibition assay, however, may be affected by various other noncyanobacterial toxins and metabolites (e.g., okadaic acid and tautomycin). Consequently, additional confirmation should be made to validate the presence of specific cyanobacterial hepatotoxins (23). ELISA is a sensitive and specific method for the detection of cyanotoxins using polyclonal or monoclonal antibodies (24). It has been successfully employed for the quantitative detection of cyanobacterial hepatotoxins including microcystin-LR, -RR, -YR, and nodularins in domestic water supplies with the detection limits of 0.05 µg L−1 for microcystin-LR in water samples, for instance (25–27). STABILITY OF CYANOTOXINS IN WATERS Cyanotoxins are normally present inside cyanobacterial cells, which enter into the water bodies during cell senescence and lysis. The release of cyanotoxins is influenced by several factors, including light intensity, application of algicide, chlorination, and the unfavorable conditions that accelerate cell death (28). Hence, the ratio of dissolved cyanotoxins to intracellular ones is different at different growth phases of cyanobacteria. In field study, the breakdown of a cyanobacterial bloom may lead to an increase of dissolved microcystins in water (29), although the concentrations detected are relatively low compared with cyanotoxins inside the cells. The existence of cyanotoxins in the aquatic environment is also affected by their stability. Factors such as temperature, pH, light intensity, and the existence of other microorganisms and oxidants with respect to their effect on cyanotoxin stability have been investigated. Anatoxin-a, for example, is stable at pH 4 for at least 21 days in reservoir water, whereas less than 5% of the original concentration was detected after 14 days at pH 8–10 (30). Microcystins and cylindrospermopsins can be oxidized by strong oxidants, for example, ozone and sodium hypochlorite (NaOCl), and their degradation under intense UV light can be accelerated by the addition of titanium dioxide (TiO2 ) (31–33). Similarly, anatoxin-a and saxitoxins are also unstable when exposed to ozone. Photolysis of microcystin may occur in the presence of humic substances and pigments of cyanobacterial cells (31,34). In addition, microcystin-LR and -RR can be degraded in vitro in bacterium Sphingomonas sp. by microcystinase (35). The degradation of nodularin can be performed with the presence of the extract of Nodularia spumigena (36). Anatoxin-a can be degraded micobiologically by Pseudomonas sp. in pure culture (37). On the other hand, microcystins and anatoxins can also adsorb onto sediments, suspended solids, and dissolved organic matters, which may correlate to the accumulation and persistence of these toxins in the environment.

to the public through contamination of drinking water, recreationally used water, and fish or shellfish. The extent of cyanotoxin poisoning can be decreased by reducing human exposure to cyanotoxins, which can be achieved through preventing toxic cyanobacterial bloom formation; monitoring of the number of cyanobacteria or the concentration of cyanotoxins in water; notifying the public of the possible hazards in the water; and providing technical and scientific advice for removal of cyanotoxins in water. The World Health Organization (WHO) has suggested the value of 1 µg L−1 for microcystin-LR in drinking water resources and provides guidelines on monitoring the number of cyanobacterial cells and the concentration of chlorophyll a in drinking and recreationally used waters, which indicates that the concentrations of microcystins can be forecasted from the densities of cyanobacterial cells if microcysin-producing cyanobacteria are dominant (38,39). Cyanobacterial blooms usually can be controlled in several ways, for example, prevention of eutrophication by reduction of external nutrient loading, control of cyanobacteria by raw water abstraction, and application of algicide. The conventional methods adopted in water treatment, including coagulation, flocculation, sand filtration, ultrafiltration, and microfiltration, are effective for removal of cyanobacterial cells from drinking water. However, the cyanotoxins may enter into water because of the lysis of cyanobacterial cells during the water treatment process. The efficiency of these methods to remove dissolved cyanotoxins in water is low (40). The more effective and practical chemical and physical methods to eliminate the contamination of dissolved cyanotoxins in water are developed based on the adsorption and destruction of the toxins. Ozonation and potassium permanganate, for example, are effective for the destruction of dissolved microcystins. The treatments by chemical oxidants, however, require optimal doses, temperature, pH, and the optimal concentrations of dissolved organic carbon (41). Although the effect of chlorination on destruction of hepatotoxins has been investigated subsequently, the efficiency of conventional chlorination in water treatment on removal of microcystins is low, which might be because of the insufficient chlorine available for microcystin oxidation. The other pertinent techniques for removal of cyanotoxins from drinking water, for example, reverse osmosis, nanofiltration, powdered activated carbon adsorption, granular activated carbon adsorption, and biodegradation, have also been investigated (42–44). However, the efficiencies of these methods for removal of different cyanotoxins are variable. No sole method regarding the removal of all types of cyanotoxins from water bodies efficiently can be adopted. The selection of the appropriate treatment method depends on the target toxin. Further investigation is required to assess the optimization of these treatment methods. BIBLIOGRAPHY

REMOVAL OF CYANOTOXINS FROM WATER Cyanotoxins may impose fatal, acute, or chronic effects on animals and humans and present a health problem

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31. Tsuji, K. et al. (1995). Stability of microcystins from cyanobacteria II: effect of UV light on decomposition and isomerization. Toxicon. 33: 1619–1631.

17. Lawton, L.A., Beattie, K.A., Hawser, S.P., Campbell, D.L., and Codd, G.A. (1994). Evaluation of assay methods for the determination of cyanobacterial hepatotoxicity. In: Detection Methods for Cyanobacterial Toxins. Proceedings of the First International Symposium on Detection Methods for Cyanobacterial Toxins. G.A. Codd, T.M. Jeffries, C.W. Keevil, and E. Potter (Eds.). The Royal Society of Chemistry, Cambridge, UK, pp. 111–116.

32. Chiswell, R.K. et al. (1999). Stability of cylindrospermopsin, the toxin from the cyanobacterium, Cylindrospermopsis raciborskii: effect of pH, temperature, and sunlight on decomposition. Environ. Toxicol. 14: 155–161.

18. Lawrence, J.F., Menard, C., and Cleroux, C. (1995). Evaluation of prechromatographic oxidation for liquid chromatographic determination of paralytic shellfish poisons in shellfish. J. AOAC Int. 78: 514–520.

34. Welker, M. and Steinberg, C. (2000). Rates of humic substance photosensitized degradation of microcystin-LR in natural waters. Environ. Sci. Technol. 34: 3415–3419.

19. Harada, K.I. (1996). Chemistry and detection of microcystins. In: Toxic Microcystis. M.F. Watanabe, K.I. Harada,

33. Senogles, P.J., Scott, J.A., Shaw, G., and Stratton, H. (2001). Photocatalytic degradation of the cyanotoxin cylindrospermopsin using titanium dioxide and UV irradiation. Water Res. 35: 1245–1255.

35. Bourne, D.G. et al. (1996). Enzymatic pathway for the bacterial degradation of the cyanobacterial cyclic peptide toxin microcystin-LR. Appl. Environ. Microbiol. 62: 4086–4094.

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36. Twist, H. and Codd, G.A. (1997). Degradation of the cyanobacterial hepatotoxin, nodularin, under light and dark conditions. FEMS Microbiol. Lett. 151: 83–88. 37. Kiviranta, J., Sivonen, K., Lahti, K., and Niemelasi, R. (1991). Production and biodegradation of cyanobacterial toxins—a laboratory study. Arch. Fur. Hydrobiol. 121: 281–294. 38. WHO. (1998). Guidelines for Drinking Water Quality. World Health Organization, Geneva. 39. WHO. (1999). Toxic Cyanobacteria in Water: A Guide to their Public Health Consequences, Monitoring and Management. World Health Organization, Geneva. 40. Falconer, I.R. (1999). An overview of problems caused by toxic blue-green algae (cyanobacteria) in drinking and recreational water. Environ. Toxicol. 14: 5–12. 41. Newcombe, G. and Nicholson, B. (2004). Water treatment options for dissolved cyanotoxins. J. Water Sup. Res. Technol.—Aqua. 53: 227–239. 42. Newcombe, G. et al. (2003). Treatment options for microcystin toxins: similarities and differences between variants. Environ. Technol. 24: 299–308. 43. Falconer, I.R. et al. (1989). Using activated carbon to remove toxicity from drinking water containing cyanobacterial blooms. J. Am. Water Works Assoc. 81: 102–105. 44. Svrcek, C. and Smith, D.W. (2004). Cyanobacteria toxins and the current state of knowledge on water treatment options: a review. J. Environ. Eng. Sci. 3: 155–184.

GROUND WATER QUALITY IN AREAS ADJOINING RIVER YAMUNA AT DELHI, INDIA CHAKRESH K. JAIN MUKESH K. SHARMA National Institute of Hydrology Roorkee, India

The groundwater quality in areas adjoining the River Yamuna at Delhi (India) has been assessed to determine the suitability of groundwater for domestic use. Thirtyeight groundwater samples from shallow and deep aquifers were collected each during pre- and postmonsoon seasons in the year 2000 and analyzed for various physicochemical and bacteriological parameters and trace elements. The study indicated concentrations of total dissolved solids, nitrate, sulfate, and sodium higher than water quality standards. The presence of total coliforms indicates bacterial contamination in the groundwater. The grouping of samples according to their hydrochemical facies indicated that the majority of the samples fall into Na-K-Cl-SO4 followed by Na-K-HCO3 and Ca-Mg-ClSO4 hydrochemical facies. The qualitative analysis of data depicted higher concentrations of various physicochemical and bacteriological parameters on the western side of River Yamuna, even in deep aquifers. INTRODUCTION Water is an essential and vital component of our life support system. In tropical regions, groundwater plays an important role within the context of fluctuating and

increasing contamination of surface water resources. Groundwater has unique features (excellent natural quality, usually free from pathogens, color, and turbidity), which render it particularly suitable for a public water supply. Groundwater also plays an important role in agriculture for watering of crops and for irrigation of dry season crops. It is estimated that about 45% of the irrigation water requirement is met from groundwater sources. Unfortunately, the availability of groundwater is not unlimited nor is it protected from deterioration. In most instances, the extraction of excessive quantities of groundwater has resulted in drying up of wells, damaged ecosystems, land subsidence, saltwater intrusion, and depletion of the resource. Groundwater quality is being increasingly threatened by agricultural, urban, and industrial wastes. It has been estimated that once pollution enters the subsurface environment, it may remain concealed for many years, disperses over wide areas of the groundwater aquifer, and renders groundwater supplies unsuitable for consumption and other uses. The rate of depletion of groundwater levels and the deterioration of groundwater quality are of immediate concern in major cities and towns of the country. The National Capital Territory (NCT) of Delhi is facing severe problems in managing groundwater quality and quantity. Surface water bodies play a significant role in groundwater flow. The hydraulic gradient has a significant role in lateral and vertical migration of contaminants in groundwater aquifers. Therefore, the present study has been carried out to assess the suitability of groundwater for domestic uses in areas adjoining the River Yamuna at Delhi and to examine the likely impact of Yamuna River water quality on groundwater. The suitability of each well for drinking has been reported in an earlier report (1). STUDY AREA Delhi generates about 1900 MLD of sewage against installed capacity of 1270 MLD of sewage treatment. The balance of untreated sewage along with a significant quantity of partially treated sewage is discharged into the River Yamuna every day. The river receives sewage and industrial wastes through various drains, which join the River Yamuna between Wazirabad and Okhla. Thus Delhi is the largest contributor of pollution to the River Yamuna, which receives almost 80% of its pollution load through these drains. The climate of Delhi is influenced mainly by its inland position and the prevalence of continental type air during the major part of the year. Extreme dryness with an intensely hot summer and cold winter are the characteristics of the climate. Only during the monsoon months does air of oceanic origin penetrate to this area and cause increased humidity, cloudiness, and precipitation. The normal annual rainfall in the National Capital Territory of Delhi is 611.8 mm. The rainfall increases from southwest to northeast; about 81% of the annual rainfall is received during the three monsoon months of July, August, and September. The balance of annual rainfall is received

GROUND WATER QUALITY IN AREAS ADJOINING RIVER YAMUNA AT DELHI, INDIA

as winter rains and as thunderstorm rain during pre- and postmonsoon months. Thirty-eight groundwater samples from shallow and deep aquifers were collected from both sides of the River Yamuna at Delhi (Fig. 1). The details of sampling locations are given in Table 1. METHODOLOGY The groundwater samples were collected in polyethylene bottles during pre- and postmonsoon seasons in the year 2000 from open wells, hand pumps, and tube wells and were preserved by adding an appropriate reagent (2,3). The water samples for trace element analysis were collected in acid-leached polyethylene bottles and preserved by adding ultrapure nitric acid (5 mL/L). Samples for bacteriological analysis were collected in sterilized high-density polypropylene bottles. All samples were stored in sampling kits maintained at 4 ◦ C and brought to the laboratory for detailed chemical and bacteriological analysis. The details of sampling locations are given in Table 1. The physicochemical and bacteriological analyses were performed following standard methods (2,3).

393

RESULTS AND DISCUSSION The National Capital Territory of Delhi has the peculiar feature of infiltration of surface water to groundwater from the River Yamuna and from various drains in addition to customary recharge from rainfall. Groundwater recharge also occurs through stagnant water pools in low-lying areas, where surface runoff water collects. The quartzite ridge, which is the prolongation of the Aravalli mountain range, forms the principal watershed in the south, southeast, and southwest parts of Delhi. Because of it, the eastern surface runoff and drainage join the River Yamuna, whereas the runoff from the western part of Delhi goes into the Najafgarh drain. The ever increasing discharge of domestic and industrial wastes into improperly lined sewage drains in Delhi leads to a high risk of contaminating the groundwater. The excessive groundwater uplift also has an adverse impact on water quality in groundwater aquifers of limited thickness. General Characteristics The hydrochemical data for the two sets of samples collected from the areas adjoining the River Yamuna at Delhi are given in Table 2. The pH in the groundwater

N

UTTAR PRADESH

ALIPUR BLOCK

KANJHAWALA BLOCK

19 17

RIVER AMUNA Y

HARYANA

SHAHDARA BLOCK 6

22 21 20 18161514 1312 DELHI 23 29 31 30 28 27 26 25 24 CITY BLOCK NAJAFGRH BLOCK

37363538343332

1

5 4 3 2 9 8 7 SHAHDARA BLOCK 10 11

MEHRAULI BLOCK

HARYANA

Figure 1. Study area showing sampling locations.

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Table 1. Description of Groundwater Sampling Locations Sample No.

Location

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

Bhagwanpur Khera Loni Road Kabul Nagar Naveen Shahdara Seelampur Shastri Park Lakshmi Nagar Prit Vihar Shankar Vihar Pratap Nagar Himmatpuri Civil Lines Rajpur road Malka Gunj Tripolia Gulabi Bagh Gulabi Bagh Shastri Nagar Shastri Nagar Lekhu Nagar Ram Pura Punjabi Bagh West Rajghat JLN Marg GB Pant Hospital Panchkuin Marg Panchkuin Marg Rajendra Nagar Rajendra Nagar Shankar Road IARI, Pusa Zoological Park Golf Course Rabindra Nagar Teen Murti Chowk Malcha Marg Sardar Patel Road Janpath

a

Type of Well (depth in ft.)a HP (25) BW (20) OW (35) HP (20) HP (30) HP (25) HP (100) TW (40) HP (200) TW (100) HP (80) TW (250) OW (25) HP (20) BW (100) BW (40) BW (160) BW (100) BW (60) HP (40) HP (40) HP (40) BW (50) HP (60) BW (20) TW (450) HP (60) BW (100) BW (300) OW (20) TW (120) HP (60) BW (80) TW (150) HP (60) BW (100) TW (150) BW (250)

HP: Hand pump; OW: open well; BW: bore well; TW: tube well.

of areas adjoining the River Yamuna is mostly within the range 6.7 to 8.3 during the premonsoon season and 6.6 to 8.2 during the postmonsoon season; most of the samples point toward the alkaline range in both seasons. The pH of all the samples is within the limits prescribed by BIS (4) and WHO (5) for various uses of water, including drinking and other domestic supplies. The conductivity varies from 628 to 3540 µS/cm during the premonsoon season and from 620 to 3250 µS/cm during postmonsoon; the conductivity of more than 70% of the samples was above 1000 µS/cm during both preand postmonsoon seasons. The maximum conductivities of 3540 and 3250 µS/cm were observed at Golf Course during the pre- and postmonsoon seasons, respectively. Higher values of conductivity in the areas nearby the River Yamuna indicate high mineralization of the groundwater. The total dissolved solids (TDSs) in the groundwater vary from 402 to 2266 mg/L during the premonsoon season and from 397 to 2080 mg/L during the postmonsoon

season. The TDSs of only about 10% of the samples analyzed were within the desirable limit of 500 mg/L. The TDSs of more than 80% of the samples were above the desirable limit of 500 mg/L. An almost similar trend was observed during the postmonsoon season. Water containing more than 500 mg/L of TDSs is not considered desirable for drinking water, though more highly mineralized water is also used where better water is not available. For this reason, 500 mg/L as the desirable limit and 2000 mg/L as the maximum permissible limit has been suggested for drinking water (4). Water containing TDSs of more than 500 mg/L causes gastrointestinal irritation (4). One sample at Golf Course (BW, 80) even crosses the maximum permissible limit of 2000 mg/L. Carbonates, bicarbonates, and hydroxides are the main cause of alkalinity in natural waters. Bicarbonates represent the major form because they are formed in considerable amount from the action of carbonates on basic materials in the soil. The alkalinity value in the groundwater varies from 116 to 380 mg/L during the premonsoon season and from 106 to 310 mg/L during postmonsoon. About 60% of the samples from the study area fall within the desirable limit of 200 mg/L, and about 40% of the samples cross the desirable limit but are within the maximum permissible limit of 600 mg/L. No sample of the study area crosses the maximum permissible limit of 600 mg/L. The high alkalinity in the study area may be attributed to the action of carbonates upon basic materials in the soil. Such water has an unpleasant taste. Calcium and magnesium along with their carbonates, sulfates, and chlorides make the water hard, both temporarily and permanently. A limit of 300 mg/L has been recommended as the desirable limit for drinking water (4). The total hardness in the study area ranges from 116 to 871 mg/L during the premonsoon season and from 114 to 792 mg/L during postmonsoon. More than 80% of the samples were found well within the desirable limits for domestic use during both pre- and postmonsoon seasons. However, one sample from Golf Course even crosses the maximum permissible limit of 600 mg/L during both seasons. The desirable limits for calcium and magnesium in drinking water are 75 and 30 mg/L, respectively (4). In groundwater in the study area, the levels of calcium and magnesium vary from 25 to 240 and from 9 to 64 mg/L, respectively, during the premonsoon season. Slightly lower levels of calcium and magnesium were observed during the postmonsoon season. In groundwater, the calcium content generally exceeds the magnesium content in accordance with their relative abundance in rocks. The increase in magnesium is proportionate to calcium in both seasons. The concentration of sodium in the study area varies from 55 to 340 mg/L during the premonsoon season and from 51 to 322 mg/L during postmonsoon. The sodium concentration of more than 50 mg/L makes the water unsuitable for domestic use. The sodium concentration was higher at all sites in the study area. The high sodium values may be attributed to base-exchange phenomena. Groundwater with high sodium is unsuitable for irrigation due to the sodium sensitivity of crops/plants.

GROUND WATER QUALITY IN AREAS ADJOINING RIVER YAMUNA AT DELHI, INDIA

395

Table 2. Hydrochemical Data of Groundwater Samples of Delhi (Pre- and Postmonsoon, 2000)a Parameter pH Conductivity, µS/cm TDSs, mg/L Alkalinity, mg/L Hardness, mg/L Chloride Sulfate, mg/L Nitrate, mg/L Phosphate, mg/L Fluoride, mg/L Sodium, mg/L Potassium, mg/L Calcium, mg/L Magnesium, mg/L MPN Coliform, per 100 mL Total count, per 100 mL Copper, mg/L Iron, mg/L Manganese, mg/L Cobalt, mg/L Nickel, mg/L Chromium, mg/L Lead, mg/L Cadmium, mg/L Zinc, mg/L a

Minimum 6.7 628 402 116 116 17 43 1.0 0.07 0.33 55 4.2 25 9.0 Nil 10 0.006 0.390 0.009 0.005 0.005 0.006 0.010 0.003 0.021

(6.6) (620) (397) (106) (114) (17) (48) (ND) (0.03) (ND) (51) (2.2) (21) (7.0) (Nil) (12) (0.003) (0.128) (0.008) (Nil) (0.009) (0.003) (0.012) (0.005) (0.012)

Maximum 8.3 3540 2266 380 841 400 690 286 0.28 1.31 340 121 240 64 2400 1850 0.178 5.740 0.944 0.034 0.043 0.033 0.064 0.010 1.110

(8.2) (3250) (2080) (310) (792) (390) (680) (287) (0.21) (0.76) (322) (103) (227) (56) (150) (540) (0.085) (5.842) (0.837) (0.037) (0.113) (0.078) (0.098) (0.021) (0.732)

Mean 7.1 1463 936 201 235 86 180 78 0.16 0.80 160 26 59 21 — — 0.023 1.960 0.162 0.016 0.028 0.013 0.033 0.006 0.320

(7.1) (1370) (879) (194) (225) (86) (177) (68) (0.08) (0.41) (157) (20) (59) (19) (—) (—) (0.012) (1.216) (0.183) (0.011) (0.028) (0.011) (0.037) (0.011) (0.190)

Values in parentheses represent postmonsoon data.

The concentration of potassium in groundwater varies from 4.2 to 121 mg/L during the premonsoon season and from 2.2 to 103 mg/L during postmonsoon. Potassium is an essential element for humans, plants, and animals and is derived in the food chain mainly from vegetation and soil. The main sources of potassium in groundwater include rainwater, weathering of potash silicate minerals, potash fertilizers, and surface water used for irrigation. It is more abundant in sedimentary rocks and commonly present in feldspar, mica, and other clay minerals. The Bureau of Indian Standards has not included potassium in drinking water standards. However, the European Economic Community has prescribed a guideline level for potassium at 10 mg/L in drinking water. Though potassium is found extensively in some igneous and sedimentary rocks, its concentration in natural waters is usually quite low because potassium minerals are resistant to weathering and dissolution. A higher potassium content in groundwater is indicative of groundwater pollution. The concentration of chloride varies from 17 to 400 mg/L during the premonsoon season. Almost the same trend was observed during the postmonsoon season. The maximum chloride content in groundwater was recorded at Golf Course. No sample in the study area crosses the maximum permissible limit of 1000 mg/L. The limits of chloride have been laid down primarily from taste considerations. A limit of 250 mg/L chloride has been recommended for drinking water supplies (4,5). However, no adverse health effects on humans have been reported from intake of waters containing a higher chloride content. The concentration of sulfate in the study area varies from 43 to 690 mg/L during the premonsoon season and from 48 to 680 mg/L during postmonsoon. Most of the

samples fall within the permissible limit (400 mg/L) for drinking water supplies. Only two samples from Himmat Puri and Golf Course exceeded the maximum permissible limit. In groundwater, sulfate generally occurs as soluble salts of calcium, magnesium, and sodium. The sulfate content of water may change significantly with time during infiltration of rainfall and groundwater recharge, which takes place mostly from stagnant water pools, puddles, and surface runoff water collected in low-lying areas. The nitrate content of drinking water is considered important for its adverse health effects. The occurrence of high levels of nitrate in groundwater is a prominent problem in NCT-Delhi. The nitrate content in the groundwater of areas adjoining the River Yamuna varies from 1 to 286 mg/L during the premonsoon season. Almost the same trend was observed during postmonsoon. Of the 38 samples analyzed, 20 samples (52.5%) had nitrate content less than 45 mg/L, whereas in about 20% of the groundwater samples, the nitrate content exceeded even the maximum permissible limit of 100 mg/L. The higher level of nitrate at certain locations may be attributed to the surface disposal of domestic sewage and runoff from agricultural fields. It has also been observed that the groundwater samples collected from hand pumps at various depths have a high nitrate content, which may be attributed to wellhead pollution. Nitrate is an effective plant nutrient and is moderately toxic. A limit of 45 mg/L has been prescribed by WHO (5) and BIS (4) for drinking water supplies. A concentration above 45 mg/L may be detrimental to human health. In higher concentrations, nitrate may produce a disease known as methemoglobinemia (blue baby syndrome), which generally affects bottle-fed infants. Repeated heavy

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GROUND WATER QUALITY IN AREAS ADJOINING RIVER YAMUNA AT DELHI, INDIA

doses of nitrates by ingestion may also cause carcinogenic diseases. Fluoride is present in soil strata due to the presence of geological formations such as fluorspar and fluorapatite and amphiboles such as hornblende, tremolite, and mica. Weathering of alkali, silicate, igneous, and sedimentary rocks, especially shales, contributes a major portion of fluorides to groundwaters. In addition to natural sources, considerable amounts of fluoride may be contributed by human activities. Fluoride salts are commonly used in the steel, aluminum, brick, and tile industries. Fluoride containing insecticides and herbicides may be contributed by agricultural runoff. Phosphatic fertilizers, which are extensively used, often contain fluorides as an impurity, and they may increase the levels of fluoride in soil. The accumulation of fluoride in soil eventually results in leaching by percolating water, thus increasing the fluoride concentration in groundwater. However, in the groundwater of the area adjoining the River Yamuna, the fluoride content was within the maximum permissible limit of 1.5 mg/L in all samples. Bacteriological Parameters The presence of coliforms in water is an indicator of contamination by human or animal excrement. The presence of fecal coliforms in groundwater is a potential public health problem, because fecal matter is a source of pathogenic bacteria and viruses. Groundwater contamination from fecal coliform bacteria is generally caused by percolation from contamination sources (domestic sewage and septic tank) into the aquifers and also by poor sanitation. Shallow wells are particularly susceptible to such contamination. The bacteriological contamination of groundwater in Delhi is mostly attributable to indiscriminate dumping of waste and garbage without any precautions or scientific disposal practices. In Delhi, most of the hand pumps withdraw groundwater from upper strata, which is most susceptible to contamination from polluted surface water. The groundwater samples collected from the area adjoining the River Yamuna in Delhi have significantly high total coliform. Bacteriological analysis indicates the presence of coliforms in more than 75% of samples during both pre- and postmonsoon seasons. The presence of coliforms was reported mostly from hand pumps. More than 30% of the samples have MPN coliforms >100 per 100 mL during the premonsoon season. Inadequate maintenance of hand pumps and unhygienic conditions around the structures may be responsible for bacterial contamination. Indiscriminate land disposal of domestic waste on the surface, improper disposal of solid waste, and leaching of wastewater from landfills further heighten the chances of bacterial contamination. Trace Elements Most of the trace metals are of immediate concern because of their toxicity and nonbiodegradable nature. Cadmium, chromium, and lead are highly toxic to humans even in low concentrations. The concentrations of heavy metals in groundwater except iron, which is present

in appreciable concentration, were below the prescribed maximum permissible limits in most of the samples. The concentration of iron varies from 0.39 to 5.74 mg/L during the premonsoon season and from 0.128 to 5.842 mg/L during postmonsoon. The concentration ranges of copper and zinc were well below maximum permissible limits. The study clearly indicated higher concentration of total dissolved solids, electrical conductivity, nitrate, sulfate, and sodium. The presence of total coliforms indicates bacterial contamination in groundwater. The presence of heavy metals in groundwater was recorded in many samples, but the levels were not significant. Water quality standards have been violated for TDSs, nitrate, sulfate, and sodium at a few places. Chadha’s Diagram for Hydrochemical Classification Chadha’s diagram (6) is a somewhat modified version of the Piper trilinear diagram (7). In this diagram, the difference in milliequivalent percentage between alkaline earths (calcium plus magnesium) and alkali metals (sodium plus potassium), expressed as percentage reacting values, is plotted on the x axis and the difference in milliequivalent percentage between weak acidic anions (carbonate plus bicarbonate) and strong acidic anions (chloride plus sulfate) is plotted on the y axis. The resulting field of study is a square or rectangle depending on the size of the scales chosen for x and y coordinates. The milliequivalent percentage differences between alkaline earth and alkali metals and between weak acidic anions and strong acidic anions would plot in one of the four possible subfields of the diagram. The main advantage of this diagram is that it can be made simply on most spreadsheet software packages. The square or rectangular field describes the overall character of the water. The diagram has all the advantages of the diamond-shaped field of the Piper trilinear diagram and can be used to study various hydrochemical processes, such as base cation exchange, cement pollution, mixing of natural waters, sulfate reduction, saline water (end product water), and other related hydrochemical problems. The chemical analysis data of all the samples collected from the area adjoining the River Yamuna in Delhi have been plotted on Chadha’s diagram (Fig. 2) and results have been summarized in Table 3. It is evident that during the premonsoon season, most of the samples fall in Group 7 (Na-K-Cl-SO4 ) followed by Group 8 (Na-K-HCO3 type) and Group 6 (Ca-Mg-Cl-SO4 ). An almost similar trend was observed during the postmonsoon season. Impact of River Water Quality on Groundwater Surface waterbodies play an important role in groundwater flow. The infiltration of surface water to groundwater usually occurs in a recharge geographical area; base flow from groundwater to surface waterbodies may occur in a discharge geographical area. In a discharge area, the hydraulic head increases with depth, and net saturated flow is upward toward the water table, but in a recharge area, the water table lies at a considerable depth beneath a thick unsaturated zone. The relationship of surface water

GROUND WATER QUALITY IN AREAS ADJOINING RIVER YAMUNA AT DELHI, INDIA

(HCO3 + CO3) − (Cl + SO4) Milliequivalent percentage

(a)

(HCO3 + CO3) − (Cl + SO4) Milliequivalent percentage

(b)

100 80 60 40 20 0 −100 −80 −60 −40 −20−20 0 20 40 −40 −60 −80 −100 (Ca + Mg) − (Na + K) Milliequivalent percentage 100 80 60 40 20 0 −100 −80 −60 −40 −20−20 0

20

40

no specific inferences could be drawn. Further studies are being planned to investigate the impact of Yamuna River water quality on the groundwater system. CONCLUSIONS 60

80

100

60

80

100

−40 −60 −80 −100 (Ca + Mg) − (Na + K) Milliequivalent percentage

Figure 2. (a) Chadha’s diagram for hydrochemical classification (premonsoon 2000); (b) Chadha’s diagram for hydrochemical classification (postmonsoon 2000).

to groundwater and its recharge/discharge characteristics may change seasonally or once during a longer time span. In deep groundwater aquifers, the movement of water from a recharge to a discharge area may take place during several years, but in shallow aquifers, recharge and discharge may be much closer and even adjacent to each other. The hydraulic gradient plays a significant role in lateral and vertical migration of contaminants in groundwater aquifers. During the present study, 38 groundwater samples were collected within 10 km of the eastern and western banks of the River Yamuna to ascertain the impact of river water on groundwater. The qualitative analysis of data showed higher concentrations of various physicochemical and bacteriological parameters on the western side of River Yamuna, even in deep aquifers. However, due to a paucity of hydrochemical, geologic, and water level data,

The suitability of groundwater in the area adjoining the River Yamuna in Delhi has been examined per BIS and WHO standards. The quality of the groundwater varies from place to place with the depth of the water table. It also shows significant variation from one season to another. Only about 10% of the total samples analyzed were within the desirable limit of 500 mg/L for TDSs, and more than 80% of the samples were above the desirable limit but within the maximum permissible limit of 2000 mg/L. From the viewpoint of hardness, more than 80% of the samples were well within the desirable limits for domestic use during both pre- and postmonsoon seasons. More than 50% of the samples had a nitrate content of less than 45 mg/L, whereas in about 20% of the groundwater samples, the nitrate content even exceeded the maximum permissible limit of 100 mg/L. The higher level of nitrate at certain locations may be attributed to the surface disposal of domestic sewage and runoff from agricultural fields. The grouping of samples according to their hydrochemical facies clearly indicates that the majority of the samples fall in Na-K-Cl-SO4 followed by Na-K-HCO3 and Ca-Mg-ClSO4 hydrochemical facies. The qualitative analysis of data showed higher concentrations of various physicochemical and bacteriological parameters on the western side of River Yamuna, even in deep aquifers. However, due to the paucity of hydrochemical, geologic, and water level data, no specific inferences could be drawn. More detailed studies including contaminant transport modeling studies are needed to understand better the impact of Yamuna River water quality on the groundwater aquifer. BIBLIOGRAPHY 1. Jain, C.K. and Sharma, M.K. (2001). Groundwater Quality in Adjoining Areas of River Yamuna at Delhi. Technical Report, National Institute of Hydrology, Roorkee, India. 2. APHA. (1992). Standard Methods for the Examination of Water and Waste Waters, 18th Edn. American Public Health Association, Washington, DC. 3. Jain, C.K. and Bhatia, K.K.S. (1988). Physico-chemical Analysis of Water and Wastewater, User’s Manual, UM-26. National Institute of Hydrology, Roorkee, India. 4. BIS. (1991). Specifications for Drinking Water, IS:10500:1991, Bureau of Indian Standards, New Delhi, India.

Table 3. Summarized Results of Water Classification Sample Numbers Classification/Type Na-K-HCO3 Ca-Mg-HCO3 Ca-Mg-Cl-SO4 Na-K-Cl-SO4

397

Premonsoon 2000 1,2,3,4,6,7,8,14,20,21 5,13 16,17,19,29,30,33 9,10,11,12,15,18,22,23,24,25,26,27,28, 31,32,34,35,36,37,38

Postmonsoon 2000 1,2,3,6,7,13,20,21 4,5 16,17,19,28,29,33 8,9,10,11,12,14,15,18,22,23,24,25,26, 27,30,31,32,34,35,36,37,38

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5. WHO. (1996). Guidelines for Drinking Water, Recommendations, Vol. 2, World Health Organization, Geneva. 6. Chadha, D.K. (1999). A proposed new diagram for geochemical classification of natural waters and interpretation of chemical data. Hydrogeol. J. 7(5): 431–439. 7. Piper, A.M. (1944). A graphical procedure in the geochemical interpretation of water analysis. Trans. Am. Geophys. Union. 25: 914–923.

CHLORINE RESIDUAL LINDA S. ANDREWS Mississippi State University Biloxi, Mississippi

Chlorine is a disinfectant added to drinking water to control microbial contamination. Both commercial water bottlers and public water systems use chlorine for this purpose. Levels added are calculated to maintain a disinfectant (chlorine) residual throughout the distribution system from the treatment facility to the end user. Historically, the disinfection and sanitation of water, food products, and food processing equipment have used halogen-containing disinfectants such as chlorine (1). The worldwide use of chlorine has improved our quality of life and prevented many disease outbreaks caused by waterborne pathogens. Chlorine was first used as a disinfectant in 1897 to treat polluted water mains after an outbreak of typhoid fever in England, and later, in 1912, it was used after a typhoid fever outbreak in Niagara Falls, New York (2). Chlorine was introduced to the food processing industries in 1935. Today, disinfection is considered to be the primary mechanism for the inactivation/destruction of many pathogenic organisms to prevent the spread of waterborne diseases to downstream users and the environment (3). Three common methods of disinfection exist in the United States and Canada: chlorination, ozonation, and ultraviolet (UV) disinfection. Chlorine, the most widely used disinfectant for municipal wastewater, destroys target organisms by oxidation of the cellular material (3). Chlorine may be applied as chlorine gas, hypochlorite solutions, or other chlorine compounds in solid or liquid form. Hypochlorous acid present in aqueous chlorine solutions is the biocidal ‘‘active chlorine’’ (4). Advantages for use of chlorination include the following (3): • Chlorination is an established method for disinfection. • Chlorination is inexpensive compared with other methods (UV and ozone). • Chlorine residuals remaining in the wastewater effluent will enhance the long-term effects of disinfection after the initial treatment and can be measured to determine the effectiveness. • Chlorine is very effective against a wide variety of microorganisms, especially enteric pathogens.

• Chlorine has the ability to oxidize certain undesirable organic and inorganic compounds. • Levels of chlorine can be adjusted according to biological load. • Oxidative capacities of chlorine can eliminate off odors during disinfection. In recent years, some health concerns have developed over the discovery of potentially carcinogenic by-products generated during chlorination in the presence of organic material. These by-products, termed ‘‘disinfection byproducts,’’ include such compounds as trihalomethanes, chloroform, and chlorophenols. Tests of chlorine-treated water have identified more than 250 compounds, approximately 10% of which have been classified as potentially mutagenic and/or carcinogenic (5). Both disinfectants and by-products can have adverse health effects (6). Other disadvantages for use of chlorination include the following (3): • Chlorine residuals, even in low concentrations, can be toxic to aquatic life and thus may require a dechlorination process. • Shipping, storage, and handling of chlorine chemicals can pose a safety risk to workers and to the environment. • Levels of dissolved solids are increased in chlorinetreated effluent. • Chlorine residuals are unstable in the presence of heavy biological load to the chlorination system, requiring increased dose applications. • Certain parasitic species known to cause problems in water supplies are relatively resistant to chlorine oxidation treatments. These species include the oocysts of Cryptosporidium parvum and the cysts of Entamoeba histolytica and Giardia lamblia as well as the eggs of some parasitic worms. • Other long-term effects of chlorination and the presence of chlorine residuals are yet unknown. Continuous chlorination is a necessity for surface water supplies from lakes, springs, ponds, or cisterns. The effectiveness of chlorine as a disinfectant is a function of contact time, the chlorine solution used, the temperature of the water and environment, and the level of residual chlorine from first introduction to the water system and continuing to the end user. Continuous chlorination typically uses a chlorine residual of 3–5 ppm. Municipalities, however, use lower levels of 0.2–0.5 ppm because they represent larger distribution systems that provide a longer contact time. Also, the higher levels of chlorine residual may cause an objectionable flavor and odor (7). Several types of chlorine residuals can be measured in treated water. Free chlorine residual is the measure of the disinfectant safety margin and is in the form of hypochlorous acid. The combined chlorine residual includes chlorine as chloramines and chlororganics that are produced when chlorine reacts with ammonia products that may be present because of biological load. The

SOURCE WATER QUALITY MANAGEMENT

total chlorine residual is the sum of free and combined residuals (7). A growing number of water systems have naturally occurring ammonia and organic contaminants in their water supplies. These contaminants react with their chlorine treatment to form the combined chlorine residuals (8). These combined residuals require up to 100 times the contact time or 25 times the chlorine concentration to be effective disinfectants in water (9). It is estimated that 3–4% of the total chlorine produced in the United States is used in potable water treatment, wastewater treatment, swimming pools, and cooling water biocide applications. Many health risks are associated with water that has not been disinfected, and health risks are associated with total residual chlorine. Residual chlorines are produced from water treatment facilities and in processing plants. Large power producing plants that use chlorinated water to prevent biofouling of heat exchangers in once-through cooling towers are also a major source of residual chlorine. Approximately 90% of such plants chlorinate cooling water on a periodic basis as compared with a continuous basis for water and wastewater treatment. Typically, chlorine is dosed at 1–2 mg/L for 20–30 minutes two to three times daily. To minimize chlorine residuals in once-through cooling systems, chlorinated effluent from one group of condensers can be blended with nonchlorinated cooling water, or targeted chlorination can be practiced (10).

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3. Solomon, C., Casey, P., Mackne, C., and Lake, A. (1998). Chlorine Disinfection, a Technical Overview. Environmental Technology Initiative, U.S. EPA. 4. Andrews, L.S., Key, A., Martin, R., Grodner, R., and Park, D. (2002). Chlorine dioxide wash of shrimp and crawfish an alternative to aqueous chlorine. Food Micro. 19: 261–267. 5. Sen, A.C., Owuso-Yaw, J., Wheeler, W., and Wei, C. (1989). Reactions of aqueous chlorine and chlorine dioxide with tryptophan, n-methyltryptophan and 3-indolelactic acid: kinetic and mutagenicity studies. J. Food Sci. 54: 1057–1060. 6. Federal Register 66FR 16858. March 28, 2001. 7. Quality Water Solutions, Chlorination. (2004). Available at: http://www.qh20.com/chlorination. 8. Spon, R. (2002). Do You Really Have a Free Chlorine Residual: How to Find Out and What You Can Do About It. RR Spon & Associates, Roscoe, IL. 9. Disinfection with Chlorine. (2004). Available at: http://www. geocities.com. 10. Lew, C.C., Mills, W., and Loh, J. (1999). Power plant discharges of total residual chlorine and trihalomethanes into rivers: Potential for human health and ecological risks. Hybrid Methods Eng. 1: 19–36. 11. USEPA (2000). Wastewater Technology Fact Sheet, Dechlorination. EPA 832-F-00-022.

SOURCE WATER QUALITY MANAGEMENT LAUREL PHOENIX

DECHLORINATION Chlorination has been used widely for disinfection of wastewater before discharge. Before the passage of the 1972 Federal Water Pollution Control Act and for several years after, significant levels of residual chlorine were routinely discharged into the environment. As the impact of the toxic by-products became known, dechlorination was instituted to remove residual chlorine from wastewater before discharge into sensitive aquatic waters (11). Dechlorination effectively removes free or total combined chlorine residuals remaining after chlorination. A common method of dechlorination is to expose the effluent to sulfur dioxide or sulfite salts. Although expensive, carbon absorption has also been used when total dechlorination is desired. State regulatory agencies set the policy for allowable levels of chlorine residuals, which effectively makes dechlorination essential for certain industries. Dechlorination protects aquatic life from the toxic effects of residual chlorine and prevents formation of harmful chlorinated compounds in drinking water. However, chemical dechlorination can be difficult to control with the potential for significant overdosing with sulfite, which suppresses the dissolved oxygen content and lowers the pH (11). BIBLIOGRAPHY 1. Biocide Int., Inc. (1994). ECO-Benefits of Oxine-A Chlorine Dioxide Based Antimicrobial. Biocide Intl., Norman, OK. 2. Sconce, J.S. (1962). Chlorine-Its Manufacture, Properties and Uses. R.E. Dreiger Publ., Malabar, FL, pp. 28–37; 514–537.

Green Bay, Wisconsin

Water utilities serving water authorities or municipalities can have many levels of control over the quality of their source waters. The more control they have over protecting the water quality of their sources, the less money they have to spend on water treatment, and the lower their risk when dealing with unforeseen emergencies. When they have no control of changing water quantities from drought, flood, or industrial pollution, they must spend more money to access backup supplies. Here, the phrase ‘‘water utilities’’ will be used interchangeably with water authorities or municipalities to refer to any local government entity providing public drinking water. HIGH CONTROL OF SURFACE WATER SOURCES Water authorities with the highest control own the entire watershed of a surface water source and protect the water quality by keeping people and development out. Others may rely on a river surrounded on all sides by a pristine forest with little or no human activity (e.g., hiking, camping) and would try to extract their water at a point just below this pristine area rather than farther downstream where other land uses could degrade the water. For utilities that cannot practicably deny access to the entire watershed or the waterbody itself, strict guidelines for land use in that area can be locally imposed instead. These guidelines can include such things as restricting the amount of impervious surfaces that can be added through development (e.g., buildings, driveways, roads), forbidding dumping of hazardous materials or

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use of pesticides, or restricting recreational activities on land and water to prevent animal waste, sediment, or fossil fuels from watercraft from contaminating the water supply. Some states grant water authorities extraterritorial land use control over land in a different municipality in order to create and enforce restrictions that will protect the water supply. HIGH CONTROL OF GROUNDWATER SOURCES Groundwater sources can be highly protected if the utility has total control over land use in the aquifer’s recharge zone. This type of control occurs when the utility owns all the land in the recharge zone, or where state or local laws require recharge zones to be fenced with signs directing people to stay out. Some states or local governments require this absolute protection of recharge zones, no matter who owns the land or what municipality has political jurisdiction. When total denial of human access or development is impossible, guidelines like the ones aforementioned can be mandated for any land lying over the recharge zone. The distance from the land surface to the water table and the substrate geology can then guide how strict the guidelines are; more restrictions being placed on land parcels overlying more vulnerable aquifers. LITTLE CONTROL OF WATER SOURCES Few water utilities have the high degree of control previously mentioned. This is because protecting surface or groundwater supplies can only be done through land use controls, and land use decisions have traditionally been the right of each local government. Therefore, most utilities may have to use a variety of strategies to deal with issues over which they have no control. This section discusses four common problems: (1) when source water is degraded, (2) when supply is uncertain, (3) when drinking water regulations are tightened, or (4) when emergency situations arise. Degraded Source Water Quality Surface waters can easily be polluted from increased drainage area development, farm runoff, or heavy rains. Development in the watershed increases erosion and causes sediment loading to surface waters. Farm runoff includes pesticides, sediment, fertilizer or manure, and silage leachate (nitrogen-rich liquid that drips from stored grains in silos). Heavy rains mobilize nonpoint source pollutants from urban landscapes, mines, farms, or silvicultural areas into water bodies. In fact, this ‘‘first flush’’ of runoff into water bodies carries high concentrations of pollutants. This multitude of diverse pollutants—sediment, chemicals, metals, pet waste, and so on—causes different kinds of problems for water treatment plants. Groundwater can be polluted for the same reasons just stated, because, except for sediment, these nonpoint source pollutants can pollute groundwater by percolating down to the water table. Groundwater can also be

degraded as the water table drops, because the quality of the water from that level may be higher in total dissolved solids (TDSs), be briny, or have arsenic or radon. Groundwater can also become unfit for use if compounds such as MTBE, perchlorate, solvents, or methane and diesel fuel from hydraulic fracturing migrate into the aquifer. Even desalting ocean water does not protect utilities from pollution problems. As coastal waters become more polluted, the costs of the reverse osmosis plants increase. Therefore, source water pollution from poor land use practices, type of geological substrate, or industrial pollutants often leaves municipalities vulnerable to forces they cannot control. Variability in Surface and Groundwater Supplies—Quantity Surface water supply quantities can vary for several reasons. First, precipitation patterns can vary from drought conditions that reduce the amount of water available to very stormy conditions that cause flooding and subsequently degrade those floodwaters with everything they come in contact with. In states with riparian water law, the drought conditions will typically cause all utilities using the same water source to equally share the burden of insufficient water. Second, well pumping next to a river or lake can reduce surface water levels for anyone next to or downstream of the pumping. If state water law has no conjunctive use rules to prevent well owners from unfairly ‘‘stealing’’ water from surface supplies, then a utility may receive less water than it expects. Third, a utility may lose access to a water source if it was leased and will not be renewed when the lease is up. And finally, in states with prior appropriation water law, a utility must consider the problems that come along with junior water rights on a stream or lake. In times of drought, a very junior right on a stream may mean it gets little or no water from that stream. If they have water rights on several streams, the different adjudication dates for each stream and the amount of water in each stream will help it calculate which streams will be able to give them how much ‘‘wet’’ water that year. In prior appropriation law, ‘‘first in time is first in right.’’ The year the right is obtained determines the order of use, so owners of earlier (and older) water rights will get their turn to use their full amount of allotted water before someone with a more junior right may divert their water. Groundwater can become inaccessible the moment other well-pumpers over that aquifer draw down the water table to a level below the water utility’s well. Consequently, the uncertainty of water supplies due to the weather, leasing versus owning a water right, or state water law rules means that utilities best serve their public by having numerous water sources available to them. In this way, diverting water from an alternate or several alternate sources protects them from inadequate water available in drought times or highly degraded water resulting from flood. If they do as Phoenix does and purchase a ‘‘water ranch’’ (a local ranch with attached groundwater rights), then they are buying not only a

DOSE-RESPONSE OF MUSSELS TO CHLORINE

water source, but a clean and nonevaporative storage site as well.

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DOSE-RESPONSE OF MUSSELS TO CHLORINE S. RAJAGOPAL G. VAN DER VELDE

New Regulation

Radboud University Nijmegen Toernooiveld, Nijmegen, The Netherlands

If new federal drinking water regulations are promulgated with lower allowable concentrations of some pollutant, then a utility’s water supply becomes automatically degraded with respect to the new regulations. Arsenic is a good example of a pollutant that recently had its maximum allowable concentrations in drinking water reduced. Utilities either must stop using that water, spend enormous amounts to clean that pollutant out of the water, or mix that water with water from another source to ‘‘dilute’’ it down to the new, acceptable drinking water standard.

V.P. VENUGOPALAN BARC Facilities Kalpakkam, India

H.A. JENNER KEMA Power Generation and Sustainables Arnhem, The Netherlands

Planning for Emergency Situations Preparing for emergencies by planning strategies is always good to do whenever possible. Water source emergencies can be a pollutant spill (e.g., fuel truck falls off highway into a river, accidental release of industrial materials into a river) or a pipeline break. These types of emergencies can only be efficiently dealt with when a utility has several sources from which to draw or sources designated as emergency backup supplies. THE FUTURE OF SOURCE WATER QUALITY MANAGEMENT Blending different source waters to upgrade quality, having multiple sources to give a utility options for accessing better quality or larger amounts, or instituting conservation to ‘‘create’’ new water are only a few strategies that utilities must employ to prepare for the future and attenuate rising costs. Future strategies to manage source waters will need a foundation of federal protection first. Not only is a significant strengthening of the Water Quality Act and Clean Water Act necessary to reduce discharges into water sources, but also much higher, and therefore effective, fines for industrial spills or NPDES permit violations need to be mandated and enforced. After this foundation is laid, there are a few additional strategies that utilities can use. Cooperative interlocal agreements can result in larger, regional water treatment systems that are more efficient. A community downstream of its surface water source or having its groundwater recharge area under a neighboring community can craft agreements to protect the supplies. For example, one community can pay another to reduce development over a recharge area by buying some of their land outright or convincing them to only use conservation subdivision designs with reduced impervious surfaces and installation of water gardens. An upstream community can be paid to improve its stormwater pollution controls or reduce land use practices that create nonpoint source pollution. For source water quality management to improve in the future, it needs not only more cooperative interlocal strategies recognizing land use regulations as the key problem to address, but also effective water pollution controls at the federal level.

Chlorine, like any other biocide, produces a dosedependent response in organisms. However, the response is dependent on a number of parameters. Chlorination of cooling water leaves residuals and by-products that are potential pollutants in the receiving water body and can impact nontarget organisms. Therefore, it is imperative to generate data on the chlorine dose–response relationships of important fouling organisms, such as various mussel species, for efficient but environmentally acceptable biofouling control. Data are presented to show the effects of mussel size (shell length), season of sample collection (spawning vs. nonspawning season), nutritional status (fed vs. nonfed), and acclimation temperature (5–30 ◦ C) on the mortality pattern of different mussel species under continuous chlorination (0.5–5 mg L−1 ). From the data, it can be concluded that although various factors can influence the dose–response relationships of mussels, generalization is not possible because of species specificity. Among the various parameters, mussel species, mussel size, status of byssal attachment, spawning season, and acclimation temperature have significant effect on chlorine tolerance of mussels, whereas nutritional status shows very little effect. INTRODUCTION Chlorination is the most commonly used disinfectant and biocide for treatment of drinking and industrial cooling water (1,2). Depending on the organisms involved and the end result desired, chlorine may be dosed either intermittently or continuously (3,4). A third important criterion that often has a bearing on the applied dose is the concentration of the chlorine (and its reaction products) that reaches the consumer (in the case of drinking water chlorination) or the environment (in the case of cooling water chlorination) (2,5). A fourth factor is chlorine demand, which exhibits variations that are both seasonal and geographical (1). Accordingly, in an actual chlorination program, the chlorine dose is modulated in such a way that the measured level of chlorine residuals is sufficient to bring about the desired result, whether it be microbiological control in drinking water or biofouling control in cooling water (6,7).

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For any given organism, one can generate a dose–response curve on the basis of how the organism responds to a given dose. However, in the case of chlorine, it is appropriate to represent this in the form of a concentration–response curve, because dosing of a certain amount of chlorine results in a variable quantity of chlorine that is available for biocidal action. In other words, the available quantity of chlorine may vary depending on the chlorine demand of the water (8). FACTORS INFLUENCING THE CHLORINE TOXICITY The response of an organism to chlorine would vary depending on a number of factors. Among the various factors, the type of organism is an important criterion. Shelled organisms (such as mussels) can withstand relatively long-term exposure to chlorinated water (9,10), when compared with soft-bodied organisms, such as hydroids or ascidians (11). A review of literature clearly indicates all other fouling organisms succumb faster than mussels. Therefore, chlorine regime targeted against mussels would also eliminate other fouling organisms. In the present review, chlorine dose–response relationships of mussels are discussed in relation with various factors, including mussel species, mussel size, spawning season, byssus attachment, nutritional status, and acclimation temperature, which can influence the chlorine tolerance of mussels. MUSSEL SPECIES Efficacy of chlorine as an antifoulant depends on various parameters, most importantly residual levels of chlorine and contact time (6,9). A survey of existing literature shows that at residual levels commonly employed (1 mg L−1 ) in power station cooling circuits, mortality takes several days. For example, at 1 mg L−1 continuous chlorination, Mytilus edulis (blue mussels) takes about 480 h for 100% mortality (12). On the other hand, in tropical marine mussels, Perna viridis (green mussels) takes about 816 h for 100% mortality when 1 mg L−1 residual chlorine is applied continuously (13). In Dreissena polymorpha (zebra mussel), 95% mortality is observed after about 552 h exposure to 1 mg L−1 residual chlorine (14). In comparison, Mytilopsis leucophaeata (dark false mussel) takes about 1104 h to achieve 100% mortality at 1 mg L−1 residual chlorine (Fig. 1). The exposure time required for 100% mortality of M. leucophaeata at different chlorine concentrations are much higher than that required for D. polymorpha (588 h) and Mytilus edulis (966 h). MUSSEL SIZE In the case of common fouling organisms such as mussels and barnacles, it is often seen that the size (or age) of the organism is an important factor that influences its sensitivity to chlorine. It has been shown that, for several organisms, a size-dependent variation in the response exists, with larger organisms showing increased tolerance

(Fig. 1). However, such size-dependent nature of toxicity is not universal and there are organisms which exhibit uniform sensitivity to chlorine, irrespective of size. An example for mussel size influencing tolerance to chlorine is the mussel M. leucophaeata (9). Here, the tolerance is maximum in medium-size mussels (about 10 mm), whereas smaller (2 mm) and larger (20 mm) mussels show greater sensitivity (Fig. 1). This pattern is in contrast with the results reported for Mytilus edulis, where the tolerance linearly increases with shell size (15). In the case of D. polymorpha, shell size has no effect on the sensitivity of the organism to chlorine (10,16). Therefore, the relationship between mussel size and chlorine toxicity is not similar among different mussel species, and generalizations regarding the size effect should be made after careful observation. BYSSUS ATTACHMENT Mussels use byssus threads to attach themselves to hard substrata. The status of attachment is also an important criterion that determines the response of mussels to chlorine (15,17). It has been experimentally shown that mussels, which normally are attached with the help of their byssus threads, become more sensitive to chlorine when they are exposed to it under unattached condition (Fig. 2). Once detached from a substratum, the mussel tries to reattach itself by producing new byssus threads, for which it has to open its bivalve shell and extend its ‘‘foot’’ outside. This kind of enhanced byssogenic activity increases the exposure of the soft tissues of the mussel to chlorine, thereby increasing the toxic effect. On the other hand, attached mussels are byssogenically less active, and in a chlorinated environment their shells remain mostly closed, thereby protecting their soft body from chlorine (12,18). SPAWNING SEASON Physiological status of the organism is also an important factor that influences chlorine toxicity. Research using a number of organisms has shown that chlorine toxicity is significantly higher during breeding seasons than during nonbreeding seasons. Mussels collected during the spawning season and those collected during nonspawning season behave quite differently with respect to their sensitivity to chlorine (Fig. 3). Mussel species collected during their spawning season were less tolerant to chlorine, whereas those collected during the nonspawning season were more tolerant. The difference in tolerance between the two groups was nearly 29% (9). Kilgour and Baker (16) and Jenner et al. (1), who reported similar results for D. polymorpha, attribute the greater tolerance of mussels during the nonspawning season to low metabolic rates and reduced filtration rates, which would result in reduced exposure to the toxicant. Lower energetic demands during nonbreeding seasons may be the reason for reduced toxicant uptake. On the other hand, mussels tend to be weaker after spawning when they have little energy reserves in the body (19), with the result that

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they are less tolerant to biocide. The data point to the importance of judicious sampling while carrying out toxicity experiments using seasonal breeders. FED VS. NONFED MUSSELS Status of feeding may have an effect on the toxicity of chlorine to organisms. Kilgour and Baker (16) showed that mussels D. polymorpha, when maintained on a diet of Chlorella, were consistently more sensitive to hypochlorite than starved mussels. The effect was attributed to an

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Figure 1. Comparison of exposure times to reach 100% mortality of different size groups of Mytilopsis leucophaeata, Dreissena polymorpha, and Mytilus edulis at different chlorine concentrations. Mortality data are expressed as mean ±SD (n = 80) of four replicate experiments (n = 20 individuals in each experiment). Test methods and mortality determinations were similar in all toxicity studies of species.

increased tendency of the fed mussels to filter water, which incidentally increases the exposure of their body parts to chlorine. Mussels that are fed with microalgae are likely to filter more water than those that are unfed. On the other hand, Rajagopal et al. (13) showed that, in the case of the mussel Perna viridis, fed and starved individuals showed similar mortality rates when exposed to chlorine. It must be kept in mind that chlorine may act as a strong suppressant of filtration activity in bivalve mussels, which has been shown by Rajagopal et al. (18) using MusselMonitor , an automated instrument with which one can

DOSE-RESPONSE OF MUSSELS TO CHLORINE

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Figure 3. Cumulative mortality (%) of spawning and nonspawning Mytilopsis leucophaeata at different chlorine concentrations (TRC = total residual chlorine). Eighty mussels were used at each chlorine dose.

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completely at residual chlorine level of 0.5 mg L−1 and higher. 1

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Figure 2. Time difference (%) between byssally attached and unattached Dreissena polymorpha (17), Mytilopsis leucophaeata, and Mytilus edulis (15) for 100% mortality at different chlorine concentrations.

monitor the opening and closing of mussel shells (1,4). Shell valve movement of M. leucophaeata tested with unfiltered brackish water from the Noordzeekanaal in The Netherlands showed little or no filtration in presence of 1 mg L−1 residual chlorine. Obviously, presence of microalgae would have no significant effect on M. leucophaeata at a residual chlorine concentration of 1 mg L−1 (Fig. 4). Rajagopal et al. (20) have also shown that filtration activity in D. polymorpha stops almost

ACCLIMATION TEMPERATURE Temperature is yet another important factor that influences the sensitivity of organisms to chlorine. Mussels acclimated to different temperatures show significantly different tolerances to chlorine (Fig. 5). Decrease in acclimation temperature from 30 ◦ C to 5 ◦ C increases chlorine tolerance (0.5 mg L−1 residual chlorine) of M. leucophaeata by 52 days. Such increase in chlorine tolerance at lower acclimation temperatures has also been reported for other mussel species, such as D. polymorpha (11,14) and Mytilus edulis (1,12). However, at acclimation temperatures above 35 ◦ C, temperature has overriding effects when compared with chlorine. Harrington et al. (21) showed that at 36 ◦ C, combined use of temperature and chlorine resulted in mortality

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Figure 5. Comparison of exposure times to reach 95% mortality of Mytilopsis leucophaeata and Dreissena polymorpha at 0.5 mg L−1 residual chlorine depending on the acclimation temperature. Triangles and circles: data of Rajagopal et al. (9); Rectangles: data of Rajagopal et al. (10). Lines are linear regressions.

of D. polymorpha at rates similar to that obtained with heat alone. CONCLUSION

control adult mussel fouling in cooling water systems? Water Res. 37: 329–338. 5. Allonier, A.S., Khalanski, M., Camel, V., and Bermond, A. (1999). Characterization of chlorination by-products in cooling effluents of coastal nuclear power stations. Mar. Pollut. Bull. 38: 1232–1241.

Data available in the literature show that various factors can influence the sensitivity of organisms estimated using chlorine bioassays. Among the parameters, mussel species, mussel size, spawning season, acclimation temperature, and status of attachment seem to have significant influence on chlorine tolerance. Therefore, chlorine bioassays using mussels or such organisms need to be carried out after taking the above factors into consideration.

6. Mattice, J.S. and Zittel, H.E. (1976). Site-specific evaluation of power plant chlorination. J. Water Pollut. Cont. Fed. 48: 2284–2308.

Acknowledgments We thank M.G. Versteeg and M. Van der Gaag for assistance with field studies. KEMA Power Generation and Sustainables, Arnhem and Schure-Beijerinck-Popping Fonds, Amsterdam, The Netherlands financially supported this research.

9. Rajagopal, S., Van der Gaag, M., Van der Velde, G., and Jenner, H.A. (2002). Control of brackish water fouling mussel, Mytilopsis leucophaeata (Conrad) with sodium hypochlorite. Arch. Environ. Contam. Toxicol. 43: 296–300.

BIBLIOGRAPHY

7. Rajagopal, S. (1997). The ecology of tropical marine mussels and their control in industrial cooling water systems. Ph.D. thesis, University of Nijmegen, The Netherlands, p. 184. 8. Rajagopal, S., Azariah, J., Nair, K.V.K., Van der Velde, G., and Jenner, H.A. (1996). Chlorination and mussel control in the cooling conduits of a tropical coastal power station. Mar. Environ. Res. 41: 201–221.

10. Rajagopal, S., Van der Velde, G., Van der Gaag, M., and Jenner, H.A. (2002). Laboratory evaluation of the toxicity of chlorine to the fouling hydroid Cordylophora caspia. Biofouling 18: 57–64.

1. Jenner, H.A., Whitehouse, J.W., Taylor, C.J.L., and Khalanski, M. (1998). Cooling water management in European power stations: biology and control. Hydroecol. Appl. 1–2: 1–225.

11. Rajagopal, S., Van der Velde, G., and Jenner, H.A. (2002). Effects of low-level chlorination on zebra mussel, Dreissena polymorpha. Water Res. 36: 3029–3034.

2. White, G.C. (1999). Handbook of chlorination and alternative disinfectants. John Wiley & Sons, Hoboken, NJ, p. 1569. 3. Claudi, R. and Mackie, G.L. (1994). Practical Manual for Zebra Mussel Monitoring and Control. Lewis Publishers, London, p. 227. 4. Rajagopal, S., Van der Velde, G., Van der Gaag, M., and Jenner, H.A., (2003). How effective is intermittent chlorination to

12. Lewis, B.G. (1985). Mussel control and chlorination. Report No TPRD/L/2810/R85, Central Electricity Research Laboratories, Leatherhead, Surrey, England, p. 33. 13. Rajagopal, S., Venugopalan, V.P., Van der Velde, G., and Jenner, H.A. (2003). Tolerance of five species of tropical marine mussels to continuous chlorination. Mar. Environ. Res. 55: 277–291.

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14. Van Benschoten, J.E., Jensen, J.N., Harrington, D.K., and DeGirolamo, D. (1995). Zebra mussel mortality with chlorine. J. Am. Water Works Assoc. 87: 101–108. 15. Rajagopal, S., Van der Velde, G., Van der Gaag, M., and Jenner, H.A. (2004). Byssal detachment underestimates tolerance of mussels to toxic compounds. Mar. Pollut. Bull. (in press). 16. Kilgour, B.W. and Baker, M.A. (1994). Effects of season, stock, and laboratory protocols on survival of zebra mussels (Dreissena polymorpha) in bioassays. Arch. Environ. Contam. Toxicol. 27: 29–35. 17. Rajagopal, S., Van der Velde, G., and Jenner, H.A. (2002). Does status of attachment influence survival time of zebra mussel, Dreissena polymorpha exposed to chlorination? Environ. Toxicol. Chem. 21: 342–346. 18. Rajagopal, S., Van der Velde, G., and Jenner, H.A. (1997). Shell valve movement response of dark false mussel, Mytilopsis leucophaeta, to chlorination. Water Res. 31: 3187–3190. 19. Bayne, B.L., Thompson, R.J., and Widdows, J. (1976). Physiology. In: Marine Mussels: Their Ecology and Physiology. B.L. Bayne (Ed.). Cambridge University Press, Cambridge, pp. 121–206. 20. Rajagopal, S., Van der Velde, G., Van der Gaag, M., and Jenner, H.A., (2002). Sublethal responses of zebra mussel, Dreissena polymorpha to low-level chlorination: an experimental study. Biofouling 18: 95–104. 21. Harrington, D.K., Van Benschoten, J.E., Jensen, J.N., Lewis, D.P., and Neuhauser, E.F. (1997). Combined use of heat and oxidants for controlling adult zebra mussels. Water Res. 31: 2783–2791.

METALLOTHIONEINS AS INDICATORS OF TRACE METAL POLLUTION TRIFONE SCHETTINO MARIA GIULIA LIONETTO Universita` di Lecce Lecce, Italy

INTRODUCTION Metallothioneins (MTs) are low molecular weight, cysteinrich metal-binding proteins that are involved in detoxification and homeostasis of heavy metals. Since their discovery in the horse kidney by Margoshes and Vallee (1), metallothioneins have been further identified in most living organisms, vertebrates, invertebrates, algae, fungi, and plants. Today, the term ‘‘metallothionein’’ is used to designate a series of well-known molecules showing a large degree of structural and functional similarities to those first described for horse kidney metallothionein. A nomenclature system for metallothionein was adopted in 1978 (2) and then extended by introducing a subdivision of all MTs into three classes (3). By this convention Class I includes metallothioneins with locations of cysteines closely related to those in the horse kidney metallothionein; Class II comprises metallothionein with locations of cysteines only distantly related to those in horse kidney metallothionein; and Class III subsumes low molecular weight metalloisopolypeptides containing

gammaglutamyl-cysteinyl units resembling in their features mammalian MTs. They are called phytochelatin and occur predominantly in plants and fungi. As the number of known MT sequences has grown, this subdivision has become inadequate. In order to better differentiate the several known MTs, in 1999 (4,5) a new classification system was proposed based on sequence similarities and phylogenetic relationships. This system subdivides the MT superfamily into families, subfamilies, subgroups, and isolated isoforms and alleles. As before, the metallothionein superfamily is defined phenomenologically as comprising all polypeptides that resemble equine renal metallothionein in several of their features (2,3). Such general features are low molecular weight, high metal content, characteristic amino acid composition (low content of aromatic amino acid residues, high cystein content, which accounts for MT heavy metal affinity and binding capacity), unique amino acid sequence with characteristic distribution of Cys (i.e., Cys–X–Cys, where X stands for an amino acid residue other than cysteine), and spectroscopic manifestations characteristic of metal thiolate clusters, which provide the protein with a highly stable tertiary structure. The metal affinity for the binding sites follows the general order found for inorganic thiolates: Hg(II) > Ag(I) > Cu(I) > Cd(II) > Zn(II). The MT superfamily is subdivided into several families, each of them including MTs that share a particular set of sequence specific characters. Members of a family can belong to only one family and are thought to be evolutionarily related. The inclusion of a MT in a family presupposes that its amino acid sequence is alignable with that of all members. A common and exclusive sequence pattern, a profile, and a phylogenetic tree can therefore be connected with each family. Each family is identified by its number and its taxonomic range. To date, 15 MT families are known: Family 1, vertebrate MTs; Family 2, mollusc MTs; Family 3, crustacean MTs; Family 4, echinodermata MTs; Family 5, diptera MTs; Family 6, nematoda MTs; Family 7, ciliata MTs; Family 8, fungi-I MTs; Family 9, fungi-II MTs; Family 10, fungi-III MTs; Family 11, fungiIV MTs; Family 12, fungi-V MTs; Family 13, fungi-VI MTs; Family 14, prokaryota MTs; and Family 15, planta MTs. BIOLOGICAL FUNCTION OF METALLOTHIONEINS The ubiquitous distribution of MTs in virtually all types of organisms studied to date attests to the conserved nature of MTs and their function. The biological function of MTs is likely related to the physiologically relevant metals that these proteins bind. In mammals, MT is found to bind zinc and copper under normal physiological conditions. Both zinc and copper are trace metals that are essential for life. Recent studies have produced strong evidence to support the idea that MT functions as a metal chaperone for the regulation of gene expression and for synthesis and functional activity of proteins, such as metalloproteins and metal-dependent transcription factors (6–10). MT could thus serve as a reservoir of essential metals. MTs are inducible proteins. Exposure of the organisms to high levels of heavy metals (e.g., Zn, Cu, Cd, and Hg) and the following increase of heavy metal cations in the

METALLOTHIONEINS AS INDICATORS OF TRACE METAL POLLUTION

cells stimulates metalloprotein neosynthesis by enhancing MT gene transcription. Cis-actin sequences, termed metal response elements (MREs), located in multiple copies along the promoter, allow heavy metal ion induction of MT transcripts (11,12). The MT mRNA is translated by cytosolic free ribosomes, leading to an increase of apometallothioneins that will rapidly react with free metal cations, sequestering them and protecting cell structures from nonspecific interaction with heavy metal cations. This process circumvents cellular damage preventing metal toxicity under overload conditions. MT induction can be measured as the concentration or rates of formation of the responsible mRNA, MT, and levels of MT-bound metals. Each of them provides different information on the inductive process and may display differential dynamics. METALLOTHIONEINS AS BIOMARKERS The importance of metallothionein (MT) in toxicologic responses to heavy metals was early recognized for potential application as a ‘‘biomarker’’ of organism exposure to heavy metals in aquatic environments. A biomarker is a pollutant-induced variation in cellular or biochemical components or processes, structures, or functions that is measurable in a biological system or sample (13). The biomarker approach in environmental monitoring has been increasingly used in the last 20 years for the ecotoxicological assessment of aquatic ecosystems. Since the harmful effects of pollutants are typically manifested at lower levels of biological organization before disturbances are realized at the population, community, or ecosystem levels (14), the use of biomarkers measured at the cellular level has been proposed as sensitive ‘‘early warning’’ tools for biological effect measurement in environmental quality assessment (15). One aspect of environmental degradation in aquatic environments is pollution from heavy metals, which are persistent and accumulable by aquatic organisms. A great number of metal pollution events have been reported in fresh waters, coastal waters, and groundwaters, where abnormal metal levels occurred as the consequence of natural and, especially, of manufactured sources of pollution. A crucial aspect of heavy metal pollution, determining the actual ecological risk, is the bioavailability of heavy metals in aquatic environments. Bioavailable heavy metals represent that portion of the total environmental metal load that is of direct ecotoxicological relevance (16). Apart from chemical analytical techniques, some other new approaches have recently been used to determine the availability of toxic metals for living organisms in aquatic environments. One of the most relevant contributions in this field is that provided by MT induction determination. Due to the interest in MT application in environmental monitoring, different techniques and methodologies have been developed in the last few years for the quantification of total MTs, including chromatographic separation of soluble cytosolic MT-containing fraction associated with the evaluation of the metal concentration, HPLC-AAS (17,18), HPLC-ICP (19–21), metal substitution assays (22,23), radioimmunological techniques (24–26), electrochemical analysis (27,28) and a spectrophotometric method recently

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developed for routine application in biomonitoring (29). Molecular biology techniques are employed for the analysis of MT mRNA. However, it is important to point out that the expression of MT levels is not implicit from the presence of endogenous MT mRNA levels in tissues. Thanks to the growing knowledge about MT quantification, induction of MT following heavy metal exposure has been reported in different aquatic species and tissues (30,31), especially in common bioindicator species such as Mytilus galloprovincialis, Mytilus edulis, Littorina littorea, Ostrea edulis, Crassostrea¨ virginica, Dreissena polymorpha, and Macoma balthica. Recent field studies using Mytilus galloprovincialis as a bioindicator have also demonstrated that measurements of MTs can provide an accurate indication of subtle environment increases in metal contamination (32,33), confirming their usefulness as a biomarker of trace metal exposure in aquatic environmental monitoring. Therefore, these proteins have been proposed by the European Commission and other international scientific organizations to be included in environmental monitoring programs as a biomarker to assess metal pollution in aquatic environments. It is known that biotic and abiotic factors such as seasonal variation, sex, age, size of the animal, and dietary factors affect MT levels in the aquatic organisms (30,34). Such factors are likely to interfere with MT synthesis in response to metal occurrence (toxic or excess of essential metals) in the aquatic ecosystems. Therefore, it is very important to know how these factors affect MT expression in the utilized bioindicator species before MT can be used in a monitoring program. Ideally, information obtained by quantification of MT in indicator species could be used to assess adverse effects on the species themselves, on other components of the ecosystem and on humans. This information could be used in routine biomonitoring programs as early warning of potential human health effects, to make decisions about possible cleanup, and to evaluate the efficacy of past cleanup of hazardous waste. BIBLIOGRAPHY 1. Margoshes, M. and Vall`ee, B.L. (1957). J. Am. Chem. Soc. 79: 4813–4814. 2. Nordberg, M. and Kojima, Y. (1979). Experientia Suppl. 34: 48–55. 3. Fowler, B.A., Hildebrand, C.E., Kojima, Y., and Webb, M. (1987). Experientia Suppl. 52: 19–22. ¨ 4. Binz, P.A. and Kagi, J.H.R. (1999). In: C. Klaassen (Ed.). ¨ Birkhauser Verlag, Basel, pp. 7–13. ¨ 5. Kojima, Y., Binz, P.A., and Kagi, J.H.R. (1999). In: ¨ C. Klaassen (Ed.). Birkhauser Verlag, Basel. 6. Maret, W. (1995). Neurochem. Int. 27: 111–117. 7. Zeng, J., Vallee, B.L., and Kagi, J.H. (1991). Proc. Natl. Acad. Sci. U.S.A. 88: 9984–9988. 8. Zeng, J., Heuchel, R., Schaffner, W., and Kagi, J.H. (1991). FEBS Lett. 279: 310–312. 9. Jacob, C., Maret, W., and Vallee, B.L. (1998). Proc. Natl. Acad. Sci. U.S.A. 95: 3489–3494. 10. Maret, W., Larsen, K.S., and Vallee, B.L. (1997). Proc. Natl. Acad. Sci. U.S.A. 94: 2233–2237.

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11. Stuart, G.W., Searle, P.F., and Palmiter, R.D. (1985). Nature 317: 828–831. 12. Hamer, D.H. (1986). Annu. Rev. Biochem. 55: 913–951. 13. NRC (National Research Council) (1987). Environ. Health Perspect. 74: 3–9. 14. Adams, S.M. (1990). Am. Fish. Soc. Symp. 8: 1–8. 15. McCarthy, F. and Shugart, L.R. (1990). Lewis Publishers, Chelsea, MI. 16. Rainbow, P.S. (1995). Mar. Pollut. Bull. 31: 183–192. 17. Suzuki, K.T. (1980). Anal. Biochem. 160: 160–168. 18. Lehman, L.D. and Klaassen, C.D. (1986). Anal. Biochem. 102: 305–314. 19. Sunaga, H., Kobayashi, E., Shimojo, N., and Suzuki, K.T. (1987). Anal. Biochem. 160: 160–168. 20. Mason, A.Z., Storms, S.D., and Jenkins, K.D. (1990). Anal. Biochem. 186: 187–201. 21. Mazzucotelli, A., Viarengo, A., Canesi, L., Ponzano, E., and Rivaro, P. (1991). Analyst 116: 605–608. 22. Scheuhammer, A.M. and Cherian, M.G. (1986). Toxicol. Appl. Pharmacol. 82: 417–425. 23. Eaton, D.L. (1982). Toxicol. Appl. Pharmacol. 66: 134–142. 24. Nolan, C.V. and Shaikh, Z.A. (1986). Anal. Biochem. 154: 213–223. 25. Roesijadi, G., Morris, J.E., and Unger, M.E. (1988). Can. J. Fish. Aquat. Sci. 45: 1257–1263. 26. Hogstrand, C. and Haux, C. (1990). Toxicol. Appl. Pharmacol. 103: 56–65. 27. Olafson, R.W. and Sim, R.G. (1979). Anal. Biochem. 100: 343–351. 28. Thompson, J.A.J. and Cosson, R.P. (1984). Mar. Environ. Res. 11: 137–152. 29. Viarengo, A., Ponzano, E., Dondero, F., and Fabbri, R. (1997). Mar. Environ. Res. 44: 69–84. 30. Bordin, G. (2000). Cell. Mol. Biol. 46(2): special issue. 31. Langston, W.J., Bebianno, M.J., and Burt, G. (1998). In: W.J. Langston and M.J. Bebianno (Eds.). Chapman and Hall, London, pp. 219–284. 32. Bebianno, M.J. and Machado, L.M. (1997). Mar. Pollut. Bull. 34: 666–671. 33. Lionetto, M.G. et al. (2001). Aquat. Conserv. Mar. Freshwater Ecosys. 11: 305–310. 34. Serafim, M.A. and Bebianno, M.J. (2001). Environ. Toxicol. Chem. 20: 552–554.

AMPHIPOD SEDIMENT TOXICITY TESTS AUGUSTO CESAR ´ MARIA DEL CARMEN CASADO MARTINEZ ´ INMACULADA RIBA LOPEZ ´ NGEL DEL VALLS CASILLAS ´ A TOMAS Universidad de Cadiz Cadiz, Spain

INTRODUCTION General Amphipod sediment toxicity tests are technically developed and are widely accepted as useful tools for a

wide variety of research and regulatory purposes (1–3). For example, they can be used to determine the sediment toxicity of single chemicals and chemical mixtures, the chemical bioavailability, the potential adverse effects of dredged material, and the magnitude and spatial and temporal distribution of pollution impacts in the field (4). Various methods have been developed to evaluate sediment toxicity and these procedures range in complexity from lethal to sublethal tests that measure effects of chemical mixtures on the amphipod species. The evaluated sediment phase may include whole sediment, suspended sediment, elutriates, or sediment extracts (5–7). The test organisms include amphipods, algae, macrophytes, fishes, and other benthic, epibenthic, and pelagic invertebrates (8). However, amphipod toxicity tests can provide rapid and effective information on the potential effects of contaminants in sediments. Historical Background Historically, the assessment of sediment quality has often been limited to chemical characterizations (9). However, quantifying contaminant concentrations alone cannot always provide enough information to adequately evaluate potential adverse effects that arise from interactions among chemicals, or that result from timedependent availability of sediment-associated contaminants to aquatic organisms (7). The evaluation of contaminant has primarily emphasized surface waters and effluents, not sediments, and the first incentive for sediment testing was dredged material (7). In 1977, the U.S. EPA and the U.S. Army Corps of Engineers recommended a series of 10-d toxicity and bioaccumulation tests with amphipods, clams, polychaetes, shrimps, and fishes to evaluate proposed discharge of dredged material into estuarine and marine waters. Significance of Use Sediment provides habitat for many benthic organisms and is a major repository for many of the more persistent chemicals that are introduced into surface waters. In the aquatic environment, most anthropogenic chemicals and waste materials including toxic organic and inorganic chemicals eventually accumulate in sediment (3). The objective of an amphipod sediment toxicity test is to determine whether contaminants in sediment are harmful to amphipod species. The tests can be used to measure interactive toxic effects of complex contaminant mixtures in sediment. The purpose of the amphipod solid-phase toxicity test is to determine if test sediment samples reduce survival (growth, reproduction, etc.) of exposed organisms relative to that of organisms exposed to control and reference sediment. Test results are reported as treatment (station) or combination of treatments (sites or chemicals) that produce statistically significant reduced survival (growth, reproduction, etc.) from control or reference sediments. Sediment amphipod tests (3) can be used to (1) determine the relationship between toxic effects and bioavailability, (2) investigate interactions among contaminants, (3) compare the sensitivities of different organisms,

AMPHIPOD SEDIMENT TOXICITY TESTS

(4) determine spatial and temporal distribution of contamination, (5) evaluate hazards of dredged material, (6) measure toxicity as part of product licensing or safety testing or chemical approval, (7) rank areas for clean up, and (8) set cleanup goals and estimate the effectiveness of remediation or management practices. Scope and Application Procedures are described for testing amphipod crustaceans in the laboratory to evaluate the toxicity of contaminants associated with sediments. Sediments may be collected from the field or spiked with compounds in the laboratory. A toxicity method is outlined for diverse species of estuarine, marine, and freshwater sediment amphipods found within coastal and fresh waters. Generally, the methods described may be applied to all species, although acclimation procedures and some test conditions (temperature, salinity, etc.) will be species specific. Procedures described here are principally based on References 1–3. Although it is recognized that a variety of other nonstandardized toxicity test methods are used in ecotoxicologic research, emphasis is placed on standardized protocols provided by the U.S. EPA and ASTM, because these are the tests most commonly used in regulatory applications (10). Other countries such as The Netherlands have adapted and developed standardized protocols using local species for regulatory purposes (11). Selection of Test Organisms The choice of a test organism has a major influence on the relevance, success, and interpretation of a test. Test organism selection should be based on both environmental relevance and practical concerns (3). The species should be selected based on sensitivity to contaminant behavior in sediment and feeding habitat, ecological relevance, geographic distribution, taxonomic relation to indigenous organisms, acceptability for use in toxicity assessment (e.g., a standardized method), availability, and tolerance to natural geochemical sediment characteristics (7).

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Amphipods have been used extensively to test the toxicity of marine, estuarine, and freshwater sediments (1–3). Ideally, a test organism should have a toxicological database demonstrating relative sensitivity to a range of contaminants of interest in sediment, have a database for interlaboratory comparisons of procedures, be in direct contact with sediment, be readily available year-round from culture or through field collection, be easily maintained in the laboratory, be easily identified, be ecologically or economically important, have a broad geographical distribution, be indigenous (either present or historical) to the site being evaluated or have a niche similar to organisms of concern (e.g., similar feeding guild or behavior to the indigenous organisms), be tolerant of a broad range of sediment physicochemical characteristics (e.g., grain size), and be compatible with selected exposure methods and endpoints. The sensitivity of an organism is related to route of exposure and biochemical response to contaminants (3). Generally, benthic organisms can receive exposure via from three primary sources: interstitial water, whole sediment, and overlying water. Because benthic communities contain a diversity of organisms, many combinations of exposure routes may be important (3). Therefore, behavior and feeding habits of a test organism can influence its ability to accumulate contaminants from sediment and should be considered when selecting test organisms for sediment testing (3). Table 1 lists some commonly used amphipod species for sediment toxicity testing and some useful information when selecting the proper amphipod species for sediment toxicity assessment. Amphipods Amphipods are ecologically important members of benthic infaunal communities and are a primary food resource for a number of marine invertebrate, fish, and bird species worldwide. In general, crustacea are among the most sensitive members of benthic communities to anthropogenic disturbance, including pollution (10).

Table 1. Some Commonly Used Amphipod Species for Sediment Toxicity Testing Amphipods Fresh water Diporeia sp. Hyalella azteca Salt water Ampelisca abdita Ampelisca brevicornis Corophium voluntator Eohaustorius estaurius Gammarus aequicauda Gammarus locusta Grandidierella jap´onica Hyalella azteca Leptocheirus plumulosus Microdeutopus gryllotalpa Repoxynius abronius Tiburonella viscana a b

Test and Point(s)a

Test Period, d

Habitatb

References

S S, G, R

10–28 10–28

B, I B, E

1,12 1,13

S, G, R S, G, R S, I S S S, R S, G S, G, R S, G, R S S S

10 10–28 10 10 10 10–28 10 10–28 10–28 10 10 10

T, I T, I T, I B, I E E T, I B, E B, I T, I B, I B, I

2,14 15,16 17,18 2,14 19,20 21,22 2,14 2,23 2,24 25,26 2,14 27,28

S = survival, G = growth, I = immobilization, R = reproduction. B = burrow, E = epibenthic, I = infaunal, T = tube dweller.

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Amphipods are a group of small crustaceans that can live in very different habitats. They are found in the sea, in estuaries, in continental waters, and even in certain terrestrial wetlands (29). Their biogeographical distribution embraces the polar waters all the way to the tropics. As for their bathymetric distribution, they extend from humid atmospheres of some forests all the way to abyssal depths. At the present time, more than 6000 species have been registered worldwide (29). Amphipods are widely distributed and common in unpolluted lotic and lentic systems; however, they are less common in hydrodynamics zones and are a primary food source for fish and voracious feeders of animal, plant, and detrital material (30). Infaunal amphipods are excellent organisms for toxicity tests with sediment (Fig. 1) and are strongly recommended as appropriate test species for toxicity bioassays (14,30,31). Amphipods are often chosen for ecological and ecotoxicological studies due to their ecological relevance, sensitivity to environmental disturbance, and amenability for culture and experimentation (2,21,32). Overall, infaunal amphipods are excellent bioassay organisms for toxicity tests with whole sediment (31). METHOD DESCRIPTION AND EXPERIMENTAL DESIGN The test system described by Swartz et al. (14) for the amphipod Rhepoxynius abronius is recommended for bioassays with this and other amphipod species. This section describes a general laboratory method to determine the toxicity of contaminated sediments using marine, estuarine, and freshwater amphipod crustaceans, following compiled standards procedures (1–3). Test sediments may be collected from marine, estuarine, and freshwater environments or spiked with compounds in the laboratory. The toxicity test usually is

Figure 1. Some species used in amphipod sediment toxicity tests.

conducted in 1-L glass chambers containing 2 cm (175 mL) of sediment and 800 mL of overlying seawater (1:4 ratio of sediment to water). For 10-d acute tests the exposure is static, and the organisms are not fed during this period. Survival is most frequently used as the endpoint in studies, and reburial of surviving amphipods is an additional measurement that can be used. However, in chronic exposure, renewal systems can be static and organisms are fed over the 28-d exposure period. The endpoints commonly used are growth and reproduction. A summary of general parameters and conditions to follow when developing an amphipod sediment toxicity test in the laboratory is included in Table 2. Quality Control If more than 10% mean mortality occurs in the control, the test must be repeated (3). However, in chronic tests 20% mean mortality in the control is acceptable. Unacceptably

Table 2. Summary of Some Conditions to Develop the Test Using Amphipods in the Laboratory Parameter Test type Temperature Salinity Light quality Illuminance Photoperiod Test chambers Sediment volume Overlying water volume Water renewal Size and life stage of amphipods Number of organisms per chamber Number of replicates Feeding regime Aeration Overlying water Test exposure Endpoints Test acceptability

Conditions Whole sediment, suspended sediment, elutriates, or sediment extracts, static or renewal (depends on test type) Species dependent (10–25 ◦ C) Species dependent (2–38 psu) Broad-spectrum fluorescent lights 500–1000 lux 24 light: 0 dark 1-L glass beakers, recommended 10 cm Ø 175–200 mL (1:4 sediment/water ratio) 600–800 mL (1:4 sediment/water ratio) Not necessary or renewal (depends on test type) Species dependent, 2–6 mm (no mature males or females) 10–20 At a minimum, 4 to 5 replicates must be used Species and test type dependent Trickle flow ( 1 mg/L or ferric > 1 mg/L or AI > 1 mg/L

Net acid water or

Settling pond Anaerobic wetland

Aerobic wetland

Settling pond or

Settling pond

Open limestone channel

Saps

Settling pond

Aeration and settling pond

Meet effluent standards? No

Re-evaluate design

Meet effluent standards? No

Yes

Yes Figure 2. Flowsheet for selection of passive treatment method (after Ref. 1).

Discharge

Anaerobic wetlands, in which the substrate for the wetland is compost and/or limestone, can be used to treat net acid water. However, the area of such wetlands must be much larger than aerobic wetlands or vertical flow ponds, so these are not common. Discharge standards for mine waters specify removal of most manganese, which can be removed passively in aerobic limestone beds (8). The influent waters must be oxidizing and have negligible concentrations of Al and Fe. In these beds, Mn-oxidizing bacteria oxidize Mn and precipitate Mn oxides and hydroxides at pH 6.5 and higher. In some such facilities, the limestone bed is inoculated with specific Mn-oxidizing bacteria (9). Recent publications indicate that periodic inspection, maintenance, and occasional rebuilding are necessary for most passive systems, especially those treating net acid water. Problems include washout during high flow, muskrat penetration of the dams, plugging of pipes by precipitates or vegetation, plugging of limestone by Al or Fe precipitates, accumulation of Fe oxides on top of compost, and channeling of flow through limited portions of the system.

BIBLIOGRAPHY 1. Skousen, J., Rose, A., Geidel, G., Foreman, J., Evans, R., and Hellier, W. (1998). A Handbook of Technologies for Avoidance and Remediation of Acid Mine Drainage. National Mine Land Reclamation Center, West Virginia University. 2. American Public Health Association (1998). Acidity (2310)/ titration method. In: Standard Methods for the Examination of Water and Wastewater, 20th Edn. L.S. Clesceri et al. (Eds.). American Public Health Association, Washington, DC, pp. 2.24–2.26. 3. U.S. Environmental Protection Agency (1979). Method 305.1, acidity (titrimetric). In: Methods for Chemical Analysis of Water and Wastes, U.S. Environmental Protection Agency Report EPA/600/4-79-020 Available at (www.nemi.gov). 4. Cravotta, C.A. and Kirby, X. (2004). Acidity and alkalinity in mine drainage: practical considerations. In: Proceedings, American Society of Mining and Reclamation, April 18–22, 2004, Morgantown, WV, pp. 334–365. 5. Hedin, R.S., Watzlaf, G.R., and Kleinmann, R.L.P. (1994). Passive Treatment of Coal Mine Drainage: U.S. Bureau of Mines, Information Circular IC 9389. 6. Kepler, D.A. and McCleary, E.C. (1994). Successive alkalinity producing systems (SAPS) for the treatment of acidic mine

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drainage. In: Proceedings, International Mine Drainage and Land Reclamation Conference, April 24–29, 1994, Pittsburgh, PA, U.S. Bureau of Mines Special Publication SP06A-94, pp. 195–204. 7. Rose, A.W. (2004). Vertical flow systems—effects of time and acidity relations. In: Proceedings, American Society of Mining and Reclamation, April 18–22, 2004, Morgantown, WV, pp. 1595–1616. 8. Rose, A.W., Means, B., and Shah, P.J. (2003). Methods for passive removal of manganese. In: Proceedings, West Virginia Surface Mine Drainage Task Force Symposium, Morgantown, WV, April 15–16, 2003, pp. 71–82. 9. Vail, W.J. and Riley, R.K. (2000). The Pyrolusite Process, A Bioremediation Process for the Abatement of Acid Mine Drainage, Vol. 30, Greenlands, pp. 40–46.

BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY ´ -DIAZ ´ M.L. MARTIN

Instituto de Ciencias Marinas de Andaluc´ia ´ Cadiz, Spain

M.C. MORALES-CASELLES ´ N. JIMENEZ -TENORIO I. RIBA T.A. DELVALLS Facultad de Ciencias del Mar y Ambientales ´ Cadiz, Spain

INTRODUCTION Contaminated sediments pose a risk to aquatic life, human health, and wildlife throughout the world. There is an overwhelming amount of evidence that chemicals in sediments are responsible for toxicological (1) and adverse ecological effects (2). Frequently, the chemicals causing these effects are present in the sediment as mixtures of organic, metal, and other types of contaminants. Identification of toxicants in sediments is useful in a variety of contexts. Adverse environmental effects from contaminated sediment resulted in international treaties and protocols for the environmental management of these dredged sediments. In this sense the OSPAR and Helsinki Conventions (North Sea, northeast Atlantic, Baltic Sea) proposed guidelines to control the disposal of sediment. Once a toxicant is identified in the sediment, steps can also be taken to link a toxicant to a discharger and prevent further discharge. In addition, identification of major causes of toxicity in sediments may guide programs such as the development of environmental sediment guidelines and, retrospectively, aid regulators in determining the type of pesticide or manufactured chemical that may cause toxicity in the field. Here, we review the use of biomarkers and bioaccumulation in sediment quality assessment. These different tools provide a more sensitive measure of bioavailability and the effects of the different contaminants in the sediment.

SEDIMENT QUALITY ASSESSMENT Sediments can act as deposits of contaminants entering the environment and, as a consequence, constitute a source of contamination. Today, remediation and management of contaminated sediments is becoming more and more economically and technologically demanding. Because of this, the scientific community has been developing sciencebased tools to identify sediments that are impaired and, ultimately, to support effective management decisions and priorities for dealing with contaminated sediments (3). When discussing the adverse effects of pollutants, some consider the accumulation of pollutant residues in the tissues of organisms to be adverse. Others consider an effect injurious only if changes occur in physiological processes in organisms, such as alterations in cellular morphology, metabolic activity, or physiological rates. Ecologists might restrict this definition still further to only those pollutant-induced effects that give rise to ecologically significant changes, that is, those at the population level (4). It is important to take into account the bioindicator species, the toxicity assay, and the different biological measurements that could show the exposure to a contaminant and the effect. Different sensitive toxicity tests have been developed to assess sediment toxicity. The different toxicity tests can group pore water and whole sediment exposure tests. These tests are conducted using benthic organisms such as amphipods, polychaetes, algae, and juvenile fish (5). Use of these organisms allows one to estimate the effect of sediment ingestion and measure bioaccumulation and different biomarkers of exposure and effect. For example, the role of sediment ingestion, which should not be underestimated, has been identified as an important route of uptake of polycyclic aromatic hydrocarbons (PAHs) by deposit-feeding benthic organisms, as shown in experiments with polychaete worms (6,7). More appropriately, three ecological life styles (filter feeding, deposit feeding, and burrowing) can be represented by the species used to assess sediment effects (8). Table 1 shows that the most appropriate phyla for potential impact testing in sediment is crustaceans, followed by annelids, mollusks, insects, fish, and echinoderms. Some of the species belonging to the taxonomic groups of crustaceans, mollusks, and fish are estuarine individuals that tolerate salinity fluctuation, which could affect the toxicity evaluation response in an environment affected by variation of physicochemical variables (9). Bioaccumulation Bioaccumulation values from different contaminant studies can help identify the bioavailability of chemicals in marine sediments and waters since, unlike chemical analysis, bioaccumulation provides a measurement of bioavailable contaminants (15). Bioaccumulation is the uptake and retention of a bioavailable chemical from any possible external source (water, food, substrate, air). It is the net result of the uptake, distribution, and elimination of a substance in an organism due to exposure in water, food, sediment, and air. For bioaccumulation to occur, the rate of uptake from

BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY

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Table 1. Summary of Species Appropriate for Testing Potential Impacts of Contaminated Sediment (10–14) Taxonomic Group Crustaceans

Name Mysid shrimp

Grass shrimp Sand shrimp Shrimp

Crab

Amphipod

Cladoceran Insects

Midge

Molluscs

Mayfly Mussel Clam

Burrowing polychaete

Annelids

Oligochaete

Echinoderms

Sea urchin

Fish

Sheepshead minnow Arrow gobi Rainbow trout Flat fish Sea bream Turbot

Test Species

Salinity Tolerance

Americamysis sp. Neomysis Americana Holmesimysis costata Palaemonetes sp. Crangon sp. Farfante penocus Pandalus sp. Sicyonia ingentis Callicnetes sapidus Cancer sp. Carcinus maenas Ampelisca sp. Rhepoxynius sp. Eohaustarius sp. Grandiderella japonica Corophium insidiosum Leptocheirus plumulosus Hyalella azteca Corophium sp. Ampelisca brevicornis Mycrodentopus Gryllotalpa Daphnia magna Ceriodaphnia dubia Chironomus tentans C. riparius Hexagenia limbata Anodonta imbecillis Yoldia limatula Protothaca staminea Tapes japonica Ruditapes philippinarum Nereis sp. Neanthes arenaceodentata Nephthys sp. Glycera sp. Arenicola sp. Abarenicola sp. Pristina leidyi Tubifex tubifex Lumbriculus variegates Strongylocentratus purparatus Lytechinus pietus Echinocardium cordatum Paracentrotus lividus Cyprinodon variegates Clevelandia ios Oncorhynchus mykiss Solea senegalensis Sparus aurata Scophthalmus maximus

M M M

all sources must be greater than the rate of loss of the chemical from the tissues of the organism (16) (Fig. 1). Toxic effects of anthropogenic compounds in biota and ecosystems are regarded in relation to their chemistry and fate in the environment. The bioavailability of chemicals, which is dependent on biogeochemical and physiological processes, is an important factor, often neglected in ecotoxicological evaluation and hazard

M, E M, E M M M M, E M, E M, E M M M, E M, E M, E, F M, E M, E M M M M F F F F F F M M M, E M M M M M M M F F F M M M M M, E M F, E M M M

assessment. The bioavailable fraction is critical for uptake and, ultimately, for the concentration at the target site in the organisms. The bioavailability of contaminants in sediments depends on several factors: physical (grain size of the sediment and suspended particulate materials), chemical (solubility, reactivity of compounds, complexing agents), and biological (benthic or pelagic organisms, mode of exposure) (17). Nevertheless, not all bioavailable

BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY

BIOMAGNIFICATION AND EFFECTS AT ECOLOGICAL LEVEL

BIOLOGICAL FACTORS Benthic or pelagic organisms, Mode of exposure, Biological fluxes

BIOAVAILABILITY

CHEMICAL FACTORS Solubility, reactivity of compounds, complexing agents, Salinity, pH

UP TAKE AND ELIMINATION

PHYSICAL FACTORS Grain size, Organic matter

ORGANISM SEDIMENT CONTAMINANTS ON TARGET TISSUES BIOACCUMULATION

MEASURE MENT OF CONTAMINANTS ON BIOLOGICAL SAMPLES

ORGANISM DEFENSE TO CONTAMINANTS (Receptor interaction, enzyme inhibition Disturbance of cell homeostasis…)

BIOMARKERS OF EXPOSURE (Metallothionein, Enzymatic activity…)

TOXICITY

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EFFECTS ON ORGANISM (Mortality, Growth reduction, Reproduction alteration, Behavioral disturbances, Mutagenicity, Carcinogenicity…)

BIOMARKERS OF EFFECT (DNA damage, Vitellogenin/Vitellin induction…)

SEDIMENT CONTAMINATION ASSESSMENT Figure 1. Ecotoxicological effects and assessment of the bioavailable fraction of pollutants in sediment.

chemicals can be bioaccumulated by the organisms in their tissues. For example, highly soluble chemicals, such as ammonia and some inorganic ions, are bioavailable and rapidly penetrate permeable tissues of marine organisms. However, they are not retained and are lost just as rapidly from the tissues by diffusion, metabolic transformation, or active transport. Other bioavailable chemicals are also taken up rapidly but are transformed and/or excreted rapidly by metabolic processes of the organism and are not bioaccumulated (16). In this sense, it is important to take into account the bioaccumulation factor (BAF), which is the ratio of the sum of the uptake rate constants of the chemical from all environmental compartments accessible to the organism to the sum of the release rate constants by active and passive mechanisms from the organism (18). The bioaccumulation factor allows one to predict if a bioavailable chemical is being bioaccumulated. Once a chemical is bioaccumulated, the concentration of the contaminant at the target tissue in the organism induces molecular manifestations of defense and the effects can be determined (Fig. 1). Persistent chemicals may accumulate in aquatic organisms through different mechanisms: via the direct uptake from water by gills or skin (bioconcentration), via uptake of suspended particles (ingestion), and via the consumption of contaminated food (biomagnification). Even without detectable acute or chronic effects in standard ecotoxicity tests, bioaccumulation should be

regarded as a hazard criterion in itself, since some effects may only be recognized in a later phase of life, are multigeneration effects, or manifest only in higher members of a food web (e.g., impact of PCBs on the hatching success of eggs) (19). Bioaccumulation of certain persistent environmental contaminants in animal tissues may be considered a biomarker of exposure (20,21). However, based on the definitions provided by Van Gestel and Van Brummelen (22), body burdens are not considered to be biomarkers or bioindicators since they do not provide information on deviations related to ‘‘health.’’ To avoid confusion, Van der Oost et al. (23) proposed that analytical–chemical indicators (body burdens) be referred to as bioaccumulation markers, while all biological (biochemical, physiological, histological and morphological) indicators measured inside an organism or its products be referred to as biomarkers. The relationship between concentration of contaminants in tissues and toxic effects measured in organisms has received increased attention during the last few decades (1). These relationships should allow one to derive tissue quality guidelines (TQGs), defined as the concentrations of the chemicals measured in the different tissues that are associated or not associated with the biological effects measured using the sediment quality guidelines (SQGs) widely used around the world (24). To identify possible toxic agent(s), one must have body burden data collected from the same organisms exhibiting toxicity.

BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY

Biomarkers Biomarkers are specific biological responses related to metabolism, detoxification, or toxicity induced by pollutants and associated with disposed materials. In this respect, an important advantage of biomarkers in assessing the impact of contaminated sediment is the inherent capability to detect early occurrence of various stress conditions within the organism and monitor the temporal progression (or regression) of the disturbance at various levels of biological organization (25). Laboratory studies have documented the use of biomarkers to provide rapid quantitative predictions of toxicity on individual organisms. At this time, the use of biomarkers is not a replacement for traditional monitoring techniques, but it can be a useful supplementary approach to demonstrate links between sublethal biochemical exposure and decreases noted in field population studies (26). A biomarker is defined as a change in a biological response (ranging from molecular though cellular and physiological responses to behavioral changes) which can be related to exposure to or toxic effects of environmental chemicals (27). Van Gastel and Van Brummelen (22) redefined the terms ‘‘biomarker,’’ ‘‘bioindicator,’’ and ‘‘ecological indicator,’’ linking them to different levels of biological organization. They considered a biomarker as any biological response to an environmental chemical at the subindividual level, measured inside an organism or its products (urine, feces, hair, feathers, etc.), indicting a deviation from the normal status that cannot be detected in the intact organism. A bioindicator is defined as an organism giving information on the environmental conditions of its habitat by its presence or absence or by its behavior. An ecological indicator is an ecosystem parameter, describing the structure and functioning of ecosystems. One of the most important features of biomarkers is that they have the potential to anticipate changes at higher levels of the biological organization (i.e., population, community, or ecosystem). Thus, these ‘‘early warning’’ biomarkers can be used in a predictive way, allowing the initiation of bioremediation strategies before irreversible environmental damage of ecological consequences occurs. Biomarkers are then defined as short-term indicators of long-term biological effects. According to the National Research Council (20) and the World Health Organization (21), biomarkers can be subdivided into three classes: biomarkers of exposure, biomarkers of effects, and biomarkers of susceptibility. The biomarkers of exposure cover the detection and measurement of an exogenous substance or its metabolite or the product of an interaction between a xenobiotic agent and some target molecule or cell that is measured in an organism. On the other hand, the biomarkers of effect show an established or possible health impairment or disease through a measurable biochemical, physiological, or other alteration in the organism. Finally, biomarkers of susceptibility indicate the inherent or acquired ability of an organism to respond to the challenge of exposure to a specific xenobiotic substance, including genetic factors and changes in receptors which alter the susceptibility of an organism to that exposure.

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New techniques allow one to detect the effects of complex mixtures of contaminants. Many are diagnostic of causes, provide information on the bioavailability of contaminants, and allow more accurate assessments of potential ecological damage. Cellular and molecular indicators provide the greatest potential for identifying individuals and populations for which conditions have exceeded compensatory mechanisms and which are experiencing chronic stress, which, if unmitigated, may progress to severe effects at the ecosystem level. The classification of biomarkers in the literature is very diffuse since biomarkers of exposure and those of effect are distinguished by the way they are used, not by an inherent dichotomy (28). Good biomarkers are sensitive indices of both pollutant bioavailability and early biological responses (23,29–31). Recently, the biomarker approach has been incorporated into several pollution monitoring programs in Europe and the United States. Likewise, different methods for biological effect measurement have been evaluated in a series of practical workshops organized by the International Council for the Exploration of the Sea (ICES) and the Intergovernmental Oceanographic Commission (IOC), such as those in the North Sea (32). The United Nations Environment Programme has founded a biomonitoring program in the Mediterranean Sea including a variety of biomarkers (10). Biomarkers have also been included in the Joint Monitoring Programme of the OSPAR convention, where Portugal and Spain are members. Nevertheless, the biomarkers approach has not been included in the guidelines for the management and monitoring of dredging and disposal activities. The current guidelines for the control of these activities are based on several approaches, which take into account chemical measurements, analysis of benthic communities, and toxicity tests. Very few studies have been done on the utility of biomarkers. In this sense, different studies on the use of biomarkers to assess the impact of contaminants on sediment (Table 2) are being carried out. Most of the studies focus on the determination of the activity of biotransformation enzymes, antioxidant enzymes, and biochemical indices of oxidative damage, DNA damage, and metallothioneins. Today, promising biomarker tools are the ‘‘genomics’’ and ‘‘proteomics.’’ In some cases genomic is used as a broad term—including proteomic—and it includes genomic sequencing, functions of specific genes, genome architecture, gene expression at transcriptome level, and protein expression at proteome level and metabolite flux (metabolomics). USING BIOMARKERS AND BIOACCUMULATION FOR REGULATION PURPOSES Frequently, the chemicals causing these effects are present in the sediment as mixtures of organic, metal, and other types of contaminants. The foundation for sediment quality assessment in the context of environmental risk assessment (ERA) is the weight-of-evidence (WOE), whose objective is to integrate multiple lines-of-evidence (LOE), both chemical and biological.

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BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY

Table 2. Biomarkers Used for Sediment Toxicity Assessment in the Laboratory, In Situ (Caged Individuals), and in the Field (11–14,26,33–36) Parameter Metallothionein GSH

DNA damage

EROD

CAT SOD GR GPX GST LPO

Vitellogenin/vitellin

TOSC Imposex, intersex

Description Induction of this protein indicates exposure to metals Assay that determines the total glutathione content, a natural antioxidant Assay that detects single-strand breaks in DNA, a measure of DNA damage Assay for ethoxyresorufin-O-deethylase, a phase I detoxification enzyme Assay for catalase, an antioxidant enzyme Assay for superoxide dismutase, an antioxidant enzyme Assay for glutathione reductase, an antioxidant enzyme Assay for glutathione peroxidase, an antioxidant enzyme Assay for glutathione-S-transferase, a phase II detoxification enzyme Assay to determine the level of thiobarbituric reactive substances from lipid peroxide breakdown Induction of this protein indicates the exposure to substances that could perturb endocrine function Total oxyradical scavenging capacity Sex change

Different tools are proposed in order to obtain multiple LOE in sediment quality assessment: (1) sediment chemistry including numeric sediment quality guidelines (SQGs), (2) toxicity tests, (3) bioaccumulation tests, (4) biomarkers, and (5) resident aquatic community structure. These tools should provide adequate estimation of the influence of the physical, chemical, and biological factors in the level of exposure and bioavailability of the different xenobiotics in the sediment (37). These tools, expressing different lines of evidence, are integrated in environmental risk assessment methodologies and utilized in monitoring and assessment sediment programs. In this regard, a tiered approach to testing is recommended. At each tier, it will be necessary to determine whether sufficient information exists to allow a management decision to be taken or whether further testing is required (8). The toxicological significance and complexity increase with each tier (Fig. 2). On Tier 0, a recompilation of information that already exists is developed. Tier I testing involves physical–chemical studies and ecotoxicological screening of the dredged material. If toxic effects are observed at Tier I (major hazard concern), the material may be evaluated on this basis. If no toxic effects are observed at this stage, but chemical analyses indicate that there may be reasons for concern, Tier II is entered and further biotests are requested. Tier II testing covers a wide range of effects parameters, including long-term and sublethal toxicity. In most cases, the Tier II results

Toxicity Assay Field, caged individuals, laboratory Field

Pollutant Response Cd, Cu, Zn, Hg, Co, Ni, Bi, Ag PAHs, PCBs

Laboratory, caged individuals

PAHs, PCBs

Laboratory, caged individuals, field

PAHs, PCBs

Caged individuals, field

PAHs, PCBs

Field

PAHs, PCBs

Laboratory, field

PAHs, PCBs

Field

PAHs, PCBs

Laboratory, field, caged individuals Laboratory, caged individuals

PAH, PCB, BNF Cd, PCB

Laboratory, caged individuals

Cd, Zn, PAHs, PCBs

Field Field, laboratory

PAHs, PCBs TBT

will allow a comprehensive evaluation of the (dredged) sediment. Only if the results are still inconclusive will it be necessary to add further tests on specific effects depending on evidence for particular contaminants, assessment of biomarkers of exposure and effect, and/or verification of laboratory measurements in the field (Tier III). Tier III testing may be used to monitor possible impacts of dredging operations in the field. The available techniques comprise nonspecific monitoring methods that respond to a wide range of environmental contaminants, biomarkers (fish, shellfish) of specific exposures depending on evidence for particular (bioaccumulation) contaminants, and assessment of long-term effects on benthos community structure and function (33). FUTURE RESEARCH NEEDS The evaluation of sediment quality in the environmental risk assessment context requires the use of more sensitive tools for sediment evaluation and the extrapolation to the field. The use of bioaccumulation and biomarkers in different bioindicator species is being researched for the assessment and management of sediment. There is an increasing consensus and interest in the valuable information that they could provide. Nevertheless, although they are more sensitive tools, they show higher variability with respect to the physical–chemical characteristics of the sediment, their extrapolation from laboratory to the field, and their intercalibration.

BIOMARKERS AND BIOACCUMULATION: TWO LINES OF EVIDENCE TO ASSESS SEDIMENT QUALITY

T I E R 0

Recompilation of information

Chemical characterization Screening tests, biomarkers of screening (eg.: Chemical and physical analysis of the sediment, Dioxins tests…)

T I E R I

T I E R II

Characterization of toxic impacts Acute tests/Chronic tests/ Biomarkers (eg.: 28-day exposure tests, amphipod mortality tests, biomarkers of exposure and effect: Metallothioneins,EROD…)

T I E R III

Verification of in situ alterations Biomarkers. Monitoring (eg.: Caged individuals, biomarkers of exposure and effect: metallothioneins, EROD, DNA damage…)

Figure 2. Schematic representation of the tier testing steps including biomarkers and bioaccumulation measurements.

In summary, some recommendations are proposed for the incorporation of biomarkers and bioaccumulation in research programs for the evaluation of dredged material quality using a weight of evidence approach: 1. Determination of biomarker screening responses to contaminated and control sediments for different sites and organisms in order to determine the advantages and disadvantages of the use of different biomarkers for the identification of different sources of contamination. 2. Study of the bioavailability of contaminants in sediment and biomarker responses through the exposure–dose–response triad methodology (exposure–chemical/biomarkers of exposure and bioaccumulation; dose/response—biomarkers of effect). It could allow the analysis of the sensitivity of different biomarkers to different availabilities of contaminants in sediment and to different contamination. 3. Measurement of biomarkers and bioaccumulation response to natural environmental conditions (pH, temperature, salinity). It could allow the application

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of biomarkers to environments that support high variability of environmental conditions, avoiding the ‘‘noise’’ that could produce this variability in a biomarker’s response. 4. Determination of biomarkers and bioaccumulation response over time through a toxicokinetic study of these responses. It could provide knowledge of biomarker and bioaccumulation behavior in the different organisms. 5. Intercalibration of bioaccumulation and biomarker responses; determination of biomarkers and bioaccumulation of the same contaminated sites in different laboratories. It could provide knowledge of the biomarkers and bioaccumulation response variation due to handling of organisms and methodology of measurement. 6. Biomarkers and bioaccumulation extrapolation from laboratory to field conditions through the determination of biomarkers and bioaccumulation response to laboratory and field contaminated toxicity exposure. These measurements could allow the analysis of responses due to realistic environmental conditions. It should be developed for three species: filter feeding, deposit feeding, and burrowing. The link between both sets of data will allow derivation of tissue quality values that need to be validated for human health and regulatory purposes. Acknowledgments This research has been partially supported by Plan Nacional I + D + I, REN2002-01699/TECNO, Ministerio de Fomento and the Spanish Ministry of Development (BOE 13-12-02) and of Education and Science (VEM2003-20563/INTER).

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University of Texas San Antonio, Texas

INTRODUCTION Lead (Pb) is a bluish white, lustrous, naturally occurring element that people have used almost since the beginning of civilization. Because of its malleability, Pb was one of the first metals that humans began to use for industrial purposes. Plumbism, or Pb poisoning, has

LEAD AND ITS HEALTH EFFECTS

been recognized for many centuries and is one of the oldest ailments afflicting humans. Nikander (200 B.C.) was first to describe the symptoms of Pb poisoning, which included colic and pallor. The English aristocracy of the seventeenth and eighteenth centuries suffered from widespread Pb poisoning from consumption of Portuguese wine, transported with submerged Pb bars to enhance flavor and to prevent spoilage. Lancereaux provided the first description of kidney disease and interstitial nephritis by postmortem examination of a Pb poisoned artist. Anthropogenic activities during the past century have resulted in increased accumulation of toxic metals in soils and natural waters (1). Lead contamination is widespread in urban areas due to industrial emissions, extensive use of alkyl-lead compounds as antiknock additives in gasoline in the past, and lead-based paints and pipes (2), resulting in soil contamination on a global scale with adverse effects on human and environmental health (3). Lead occurs naturally in low concentrations in all rocks, soils, and dust, usually ranging from 2 to 200 ppm (4). The periodic position of Pb favors the formation of covalent rather than ionic bonds in Pb4+ compounds. Lead is similar to certain alkaline earth metals, particularly calcium. Both calcium and Pb form insoluble carbonates and phosphates. However, Pb carbonates and phosphates are less soluble compared to those of calcium. This insolubility of Pb together with its high affinity to biological donors (enriched in oxygen and possibly nitrogen) accounts for its toxicological properties (5). Here, we provide an overview of the various sources of Pb, its impact on the ecosystem and its effects on human health. Future directions in research related to the effects of Pb on human health are also discussed. SOURCES OF LEAD Natural Sources The average concentration of Pb in the earth’s crust is estimated to be 16 mg/kg (4). Lead is mainly found in the form of its sulfide, galena. Some other ores of Pb include cerussite and anglesite. In general, granitic rocks that have high acidic content tend to have more Pb than basaltic rocks. Lead concentrations in soils (farming and city) range from 2 to 200 mg/kg, with most soils having Pb in the range of 5–25 mg/kg (6). Moreover, soils that are underlain by granitic rocks with high acid content have higher Pb concentrations than those overlying basaltic and other alkaline rocks (6). It has been estimated that global natural emissions of Pb to the atmosphere are in the range of 18.6–29.5 × 106 kg/yr. Anthropogenic Sources The major anthropogenic sources of Pb are industrial activities such as mining operations (nonferrous metal, secondary Pb smelters), vehicle emissions, coal burning, refuse incineration, and industrial outdoor paints applied to structural surfaces. However, with the phasing out of Pb in gasoline (which began in the 1970s), Pb in soils and house dusts originating from lead-based paints have

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become the principal sources of exposure in the United States (7). In rivers or water bodies, the concentration of Pb mainly depends on local inputs. Since most Pb compounds have low solubility, high concentrations are very rare. However, they are found in acid mine drainage in high concentrations mostly in areas of Pb mineralization (8). Lead shots used for hunting and fishing can also result in significant Pb input to both soil and water and contribute to inputs to surface waters (9), ultimately adding to the Pb burden in the sediments. MOVEMENT OF LEAD IN THE ENVIRONMENT The passage of metals through the atmosphere is integral to their biogeochemical cycling. Because of the dynamic nature of the atmosphere, metals can be deposited in areas remote from their initial source. Air is the primary medium for the transport of Pb. Fine particles of Pb generated anthropogenically are transported over long distances until they settle through wet, dry, or cloud deposition (5). Lead transport in the environment depends on the size of the particles. While larger particles (comprising 95% of the emission) settle down after sometime, the smaller Pb particles can travel hundreds of kilometers before they are deposited (4). Lead in the soil and dust is relatively unavailable biologically. It normally reacts with the soil to form insoluble salts. Moreover, Pb also complexes with components of organic matter such as humic acid and fulvic acid, thus making Pb more unavailable (6). The downward movement of Pb from soil by leaching is very slow under most natural conditions (10). Mobility of Pb in the soil is dictated by a number of geochemical process, including oxidation/reduction, precipitation/dissolution, adsorption/desorption, and complexation/chelation. Metallic Pb can be oxidized to more labile forms, the rate of oxidation and the oxidation products being dependent on the site. Once Pb is oxidized, it can be precipitated in the form of hydroxides, sulfates, sulfides, carbonates, and phosphates. The solubility of these precipitates is dependent on factors such as pH and oxidation–reduction conditions. In general, Pb is more soluble under acidic conditions compared to neutral and alkaline conditions. Most of the Pb accumulated in the soil may be directly taken up by grazing animals and microorganisms or may be ingested by children through hand-to-mouth activity. From the grazing animals Pb may enter the food chain (5). Lead in rivers comes from runoff, erosion, and direct deposition from air. Fresh water generally contains more inorganic and organic suspended material than marine water, and this suspended material has a tendency to adsorb any dissolved Pb. In the case of the oceans, most of the Pb comes from atmospheric deposition rather than from rivers (4). ECOTOXICOLGICAL EFFECTS OF LEAD The uptake of Pb in both aquatic and terrestrial ecosystems is determined by its bioavailability. The term ‘‘bioavailability’’ reflects the premise that, for some

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heavy metals, organisms may be exposed to less than the total amount present in their habitat (11). The extent to which heavy metals react with and affect biological components is immensely influenced by the physicochemical factors of the specific environment (12). In general, the systemic availability of Pb is matrix and chemical species dependent (13–15). Toxicity to Aquatic Organisms Dose-related increases in lead concentrations of submerged and floating plants have been observed upon their exposure to dissolved Pb, accumulation being the greatest in the roots, followed by stems and leaves (16). In a study conducted by Kay et al. (17) water hyacinth (Eichhornia crassipes) was exposed to solutions containing lead nitrate concentrations of 0–5 mg/L for 6 weeks. The accumulation of Pb was dose-dependent and in the order of roots > stems > leaves. Uptake of Pb from shotcontaminated sediments has been observed in aquatic plants. In an investigation of a skeet target shooting range located on the shores of Lake Merced, California, sediments contained Pb levels up to 1200 µg/g in the shotfall zone, and tule seedheads and coontails growing within these sediments exhibited Pb concentrations averaging 10.3 and 69.2 µg/g dry weight, respectively, compared to concentrations of 2.3 and 11.9 µg/g dry weight, respectively, at control sites (18). However, Van der Werff and Pruyt (19) reported that application of lead nitrate with a Pb concentration of up to 10−5 mol/L had no observable toxicity on four aquatic plants, Elodea gibba, Callitiche platycarpa, Spirodela polyrhiza, and Leman gibba. In the case of fishes, it has been found that in vivo sublethal dietary doses of Pb (II) and tributyltin (TBT) induced toxic effects in H. malabaricus (20). Davis et al. (21) conducted long-term bioassays with rainbow trout to establish a maximum acceptable toxicant concentration (MATC) limit for inorganic Pb. Fingerling trout were exposed to nominal total Pb concentrations of 0, 40, 120, 360, 1080, or 3240 mg/L. Actual dissolved Pb was measured and results were expressed in terms of dissolved salt. They reported that MATC values between 0.018 and 0.032 mg/L caused the ‘‘black tail effect.’’ A similar bioassay with soft water in fishes hatched from exposed eggs suggested MATC values between 0.041 mg/L (where no black tails occurred) and 0.076 mg/L (where 4.7% of fish showed the black tail effect). When fingerlings from nonexposed eggs were used in a soft water bioassay, the MATC for the black tail effect was between 0.072 mg/L (where no black tails occurred) and 0.146 mg/L (where 41.3% of fish had black tails). There were no significant differences between the measured dissolved Pb concentrations in the two tests, indicating that fish from exposed eggs were more sensitive to the effects of Pb than those from nonexposed eggs. Maddock and Taylor (22) investigated the uptake of organolead by shrimp, mussel, and dab (a flat fish) in short-term experiments and in mussel and dab in longterm experiments. Bioconcentration factors were higher for tetraalkyl Pb than for trialkyl Pb in the shortterm exposure. In the long-term experiment conducted on mussels, the greatest tissue concentration of Pb occurred

in the gills; with the digestive glands, gonads, and feet containing progressively less Pb (17). Toxicity to Terrestrial Organisms Toxicity to Plants. Although Pb is considered to be toxic to plants just like other life forms, sensitivity of plants to Pb and responses of different plant species to Pb vary according to their genetic and physiological makeup (23). The metal remains largely as a superficial deposit or topical aerosol coating on plant surfaces (24,25). Toxicity of Pb to a large extent depends on its absorption, transport, and cellular localization (23). Plants of Cassia tora and C. occidentalis growing by the roadside accumulated up to 300 mg/g dry weight of Pb (26). Furthermore, accumulated Pb content generally increases with the increase in Pb in the environment, as has been reported for maize and pea leaves and Vigna and sesame roots (23) and leaves (27, 28). Photosynthesis is considered as one of the most sensitive metabolic processes to Pb toxicity (23). Moreover, nitrate reduction is inhibited drastically in roots by the metal, but in the leaves a differential effect is observed in various cultivars (23). Nitrate assimilation is inhibited by 10–100 mM Pb2+ in sorghum leaves (29). Lead also inhibits nodulation, N fixation, and ammonium assimilation in the root nodules (23). Toxicity to Invertebrates. Long-term exposure of terrestrial invertebrates to lead-contaminated soil can result in high tissue concentrations, but one of the detoxification mechanisms within their cells is the subcellular compartmentalization of Pb. This results in only a fraction of the total body Pb burden actually contributing to toxicity (30). Doelman et al. (31) incubated a mixed culture of bacteria in lead nitrate solutions and also grew the fungus Alternaria solani on malt agar to which lead nitrate had been added. The cultures were used as food for the nematodes Mesorhabditus monohystera and Aphelenchus avenae, which were reared for up to 22 days on bacteria and fungus, respectively. Lead was taken up by bacteria to give a range of doses to the nematodes of between 7.6 and 110 µg/g of food. All these exposures had a significant inhibitory effect on the reproduction of Mesorhabditus monohystera. However, when woodlice (Porcellio scaber) were exposed to treated soil litter containing between 100 and 12,800 mg/kg dry weight of Pb as lead oxide over 64 weeks, no significant effect was found on adult survival, number of young produced, or the survival of the young at exposures up to 6400 mg lead/kg (32). Toxicity to Birds. In the case of birds, metallic Pb is highly toxic when it is given in the form of Pb shots. Lead poisoning through the ingestion of spent gunshots is a widely recognized waterfowl mortality factor (33). Water fowl ingest spent gunshot when searching for grit (and possibly for food) particles. Once in the bloodstream, Pb is rapidly (but reversibly) deposited in soft tissues, mainly liver and kidney, and (relatively irreversibly) into bone (34). If a large quantity of Pb (e.g., >10 shots) is ingested within a short time, acute Pb poisoning may occur, resulting in death within a few days. However, most of the mortality results from the ingestion of a smaller

LEAD AND ITS HEALTH EFFECTS

number of shots, with birds dying of chronic poisoning 2–3 weeks following ingestion (34). The U.S. Fish and Wildlife Service (35) reported that Pb poisoning from ingested sinker and jigs accounts for 10–15% mortality of common loons (Gavia immer) with a study revealing that 27% of adult loons had fishing tackle in their stomachs and high Pb levels in their blood. Signs of chronic Pb poisoning include green and watery feces, dropping wings, anemia, weight loss, and atypical behavior; the affected birds die approximately 2–3 weeks after ingesting the shot, often in a very weak condition (36). Secondary Pb shot poisoning can occur when a predator or scavenger consumes animals that have been shot with Pb shot shell ammunition or consumes the gizzard of a bird that has ingested Pb shot (36). Lead also causes a decrease in clutch and egg size, mortality of embryos, depression of growth, and deficits in behavior, thus affecting the survival of birds (37). EFFECTS ON HUMANS Lead is present in various forms in the environment, such as free hydrated ions, ion-pair salts/complexes, and organic complexes/chelates (38). Humans are most likely to be exposed to the inorganic forms of Pb such as halides, oxides, sulfides, carbonates, and chromates. Since Pb was phased out as a gasoline additive (tetraethyl Pb) in the 1970s and its use in paint and food containers (e.g., ceramic ware and tin cans) was curtailed, blood Pb concentrations (BLLs) have decreased significantly. However, other sources of Pb and its unknown threshold of subclinical toxicity continue to make Pb an issue of public health concern (39). Lead exposure in the general population (including children) occurs primarily through ingestion, although inhalation also contributes to Pb body burden and may be the major contributor for workers in Pb-related occupations (40). Children’s hand-to-mouth activity, increased respiratory rates, and increased intestinal absorption of Pb make them more susceptible to Pb exposure than adults (41,42). Exposure to Pb can result in significant adverse health effects to multiple organ systems. Once Pb is absorbed into the blood plasma, it rapidly equilibrates with the extracellular fluid. More slowly, but within minutes, Pb is transferred from plasma into blood cells (43,44). From the blood plasma, the absorbed Pb is transferred to the liver and the kidneys. Lead tends to accumulate in areas with high levels of calcium; hence, the highest body burden of Pb is found in the bones. In a typical adult, 95% of the Pb is stored in the bones, whereas in children, it amounts to 70% (45,46). During childhood, Pb accumulates predominantly in the trabecular bones. But in the case of adults most of the Pb is found in both cortical and trabecular bones. In both the trabecular and cortical bones there are two physiological compartments, one labile and the other inert for Pb (7). While Pb may be exchanged between the blood and the bone through the labile component, Pb may be stored for years in the inert component (7). The distribution of Pb in tissues reflects a state of constant, dynamic equilibrium. Any situation that mobilizes the very large, relatively stable pools of Pb

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within the body, particularly those in the bones, will lead to the redistribution of Pb to a variety of tissues. Redistribution is known to occur during pregnancy, which results in increased risk to the fetus, particularly in women with prior Pb poisoning (5). The various detrimental human health effects of Pb include: • Neurological effects including effects on the central and peripheral nervous systems. • Effects on both male and female reproduction. • Renal effects. • Effects on vitamin D metabolism. • Cardiovascular effects. • Hematopoietic effects. Neurological Effects Lead affects both the central and peripheral nervous systems. An extensive database has provided a direct link between low level Pb exposure and deficits in the neurobehavioral–cognitive performance evidenced in childhood through adolescence (47). Many of the biological aberrations produced by Pb appear to be related to the ability of this heavy metal to either inhibit or mimic the action of calcium. Calcium ions play a special role in the release of neurotransmitters from presynaptic nerve endings (48). A large number of experimental studies have investigated the effects of prenatal and neonatal Pb exposure on central nervous system development and behavior. These studies have shown variable results, forming a spectrum that includes delayed nervous system development, deficits in visual motor function, abnormal social and aggressive behavior, hyperactivity and hypoactivity, as well as no changes in activity (49). The brain and the nervous systems of children and fetuses are generally vulnerable to Pb intoxication because of the incomplete blood–brain barrier and also because both the brain and the nervous system are still developing (40). Effects on Central Nervous System In the central nervous system, Pb toxicity is more common in children than adults and may produce either overt symptoms of acute encephalopathy, such as ataxia, headache, convulsions, and coma, or lesser deficits including learning disorders and hyperactive behavior (50,51). Lead disrupts the main structural components of the blood–brain barrier through primary injury to astrocytes with a secondary damage to the endothelial microvasculature. Within the brain, lead-induced damage occurs preferentially in the prefrontal cerebral cortex, hippocampus, and cerebellum (47) Lead enhances the spontaneous or basal release of neurotransmitters from presynaptic nerve endings at low concentrations (48). In addition to enhancing the spontaneous release of neurotransmitters, Pb blocks the release of neurotransmitters normally produced by depolarization of nerve endings. It modulates neurotransmitter release by altering calcium metabolism either by competing with calcium for entry into the cell or by increasing intracellular calcium levels (48). Moreover, high dose exposure to Pb (i.e., BLLs in excess of

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4 µM) disrupts the blood–brain barrier (48). In general, blood–brain barrier excludes plasma proteins and most organic molecules and limits even the passage of ions such as sodium and potassium (52). However, at high BLLs large molecules such as albumin, which are normally excluded, freely enter the brain of immature animals exposed to high concentrations of Pb (53,54). Ions and water follow and edema is produced, resulting in the rise of intercranial pressure because of the physical restraint of the skull. When the intercranial pressure approaches the systemic blood pressure, cerebral perfusion decreases and brain ischemia occurs (48). Children exposed to high levels of Pb suffer from encephalopathy and hyperirritability, ataxia, convulsions, stupor, and coma or death. In general blood, BLLs of about 70–80 µg/dL or greater in children pose a threat (7). However BLLs as low as 10 µg/dL or less can adversely affect the developing nervous system of a child (40). Studies have shown that for every 10 µg/dL increase in the BLL, there is a decrease of children’s IQ by about four to seven points (55–60). In the case of adults, Pb encephalopathy may occur at BLLs of about 460 µg/dL (61). Effects on Peripheral Nervous System Peripheral neuropathy is a manifestation of Pb toxicity in adults with excessive occupational exposure. Children exposed to high levels of Pb may also suffer from peripheral neuropathy. While in adults the most common manifestation of peripheral neuropathy is wrist drop, in the case of children, general weakness and foot drop are more common (62). Effects of Lead on Reproduction Male Reproductive System. An adverse effect of Pb on the male reproductive system has been reported in several epidemiologic studies (63). It has been reported that BLLs below the currently accepted working protection criteria adversely affect spermatogenesis (64). Earlier studies on Pb workers had shown androgenic dysfunction including asthenospermia, hypospermia, and teratospermia that could be produced by direct toxicity to the testis (65). It has been shown that significant levels of asthenospermia and teratospermia were found in workers having BLLs over 500 µg/L (66). The effect of Pb poisoning on the male reproductive system can be seen at BLLs of about 40 µg/dL, with long-term Pb exposure resulting in diminishing sperm counts, sperm concentrations, and total sperm motility (7). Moreover, it was found that the risk of stillbirth or birth defects was elevated for preconception employment in a high Pb exposure environment compared with low Pb exposure jobs (67). Female Reproductive System. There have been few well-documented reports on reproductive effects of Pb in humans (68). Exposure may result in increased preterm delivery. It was found that preterm delivery was statistically significantly correlated with maternal BLLs in a dose-responsive manner (69). Moreover, due to changes in the bone physiology and mineral metabolism

during pregnancy, Pb may move from the bone into the maternal circulation. Lead does cross the human placenta as early as the 12th week of gestation (70). Cord-blood content of Pb shows a high correlation with maternalblood samples, suggesting that infants are exposed in uterus to BLLs equivalent to those of the mother (71). Recent isotopic speciation studies have demonstrated that the skeletal contribution to BLLs increases from 9% to 65% during pregnancy (72). The maternal Pb burden has been reported to be negatively associated with the birth weight of infants (73). It has been found that prenatal exposure to low Pb levels (e.g., maternal BLLs of 14 µg/dL) may increase the risk of reduced birth weight and premature birth (7). Effects on the Renal System Lead affects the renal system in three stages. In the first stage, there is proximal tubular dysfunction (Fanconi’s syndrome) manifested by aminoaciduria, glycosuria, and phosphaturia (74). Then chronic exposure results in the second stage that is characterized by gradual tubular atrophy and interstitial fibrosis. There is reduced incidence of inclusion bodies, and glomerular filtration is impaired (75). At the third stage, renal failure occurs and is characterized by renal tubular neoplasia or adenocarcinoma (76). In general, individuals with Pb levels exceeding 60 µg/dL are at a risk of developing renal failure (77,78). It has been reported that Pb inhibits rBAT-induced amino acid transport in a noncompetitive, allosteric fashion. This blockade of rBAT-induced amino acid transport may be involved in aminoaciduria following Pb intoxication (79). Lead exposure also results in the onset of ‘‘saturnine gout’’ as a result of lead-induced hyperuricemia due to decreased renal excretion of uric acid. Most documented renal effects for occupational workers are observed in acute and high to moderate chronic exposures with BLLs of more than 60 µg dL (40). Endocrine Effects/Effects on Vitamin D Metabolism From the studies of children exposed to high Pb levels, it has been found that a correlation exists between BLLs and the level of vitamin D. Lead interferes with the conversion of vitamin D to its hormonal form, 1,25-dihydroxyvitamin D, which is responsible for the maintenance of extracellular and intracellular calcium homeostasis. Thus, impairment by Pb results in impaired cell growth, maturation, and tooth and bone development (40). Cardiovascular Effects Lead exposure is one of the factors that may contribute to the onset of hypertension. Other factors contributing to the development of hypertension include old age, increased weight, poor diet, and excess alcohol intake (40). Studies have shown that greater exposure to Pb in occupational environments may increase the risk of hypertensive heart disease and cardiovascular disease. There are several reports that have associated Pb exposure to elevation in blood pressure (80–83).

LEAD AND ITS HEALTH EFFECTS

Hematopoietic Effects Lead inhibits the body’s ability to make hemoglobin by interfering with several enzymatic steps in the heme pathway (40). Heme is the prosthetic group of hemoglobin, myoglobin, and cytochromes. In mammals, heme is synthesized from succinyl-CoA and glycine in eight enzymemediated steps (Fig. 1) (84). Enzyme studies of the heme biosynthetic pathway have shown that Pb is an inhibitor of δ-aminolevulinate dehydratase (ALAD), corporphyrinogen oxidase, and ferrochelatase (85). However, the metal has the greatest influence on ALAD, and measurement of ALAD activity can be used as an indicator of Pb levels in the blood (84). Heme synthesis occurs partly in mitochondria and partly in cytoplasm. The three important steps in the synthesis of heme that are influenced by Pb intoxication are: 1. The condensation reaction of two molecules of δ-aminolevulinic acid that is catalyzed by PBG synthase (porphobilinogen synthase) or ALA dehydratase to form porphobilinogen (PBG). ALA-D is the enzyme that is most sensitive to Pb. Inhibition of the enzyme results in the prevention of the utilization of ALA and subsequently a decline in heme synthesis (68). 2. The rate-limiting step in heme biosynthesis is the ALA synthase catalyzed step. The oxidation product of heme is hemin, which acts as a negative feedback inhibitor of ALA synthase and inhibits the transport of ALA synthase from the cytosol to the mitochondria and also represses the synthesis of the enzyme. Lead interferes with the negative feedback control of heme synthesis; ALA synthetase activity is depressed, resulting in increased activity of the enzyme and increased synthesis of ALA (68). 3. The third reaction that is influenced by the intoxication of Pb is the incorporation of the

Inside mitochondria

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ferrous iron into the porphyrin ring structure that is catalyzed by the enzyme ferrochelatase. Lead inhibits the enzyme ferrochelatase, thus preventing the introduction of iron into the protoporphyrin IX to form heme. The porphyrin chelates with Zn nonenzymatically to form ZnPP, which in turn is incorporated into hemoglobin. It has been found that ZnPP containing hemoglobin has a much lower oxygen capacity than Fe-containing hemoglobin (68). Moreover, iron in the form of ferritin and ferruginous micelles also accumulate in the mitochondria of bone marrow reticulocytes (68) (Fig. 1). In general, Pb induces two types of anemia. While acute, a high Pb level results in hemolytic anemia; chronic Pb exposures result in anemia that is induced by the interference of Pb with heme biosynthesis and also by diminished red blood cell survival. According to the EPA, in the case of occupationally exposed adults, the threshold BLL for a decrease in hemoglobin is 50 µg/dL, whereas in children, the threshold BLL has been observed to be 40 µg/dL (7). FUTURE DIRECTION Lead is ubiquitous in nature, but anthropogenic activities have further exacerbated Pb levels in the environment. Although lead-based petroleum has been phased out, Pb is still being used in the industry (such as lead-acid battery manufacturing industry) due to the absence of viable alternatives. Blood lead levels of 10 µg/dL have been associated with adverse health effects in children (86). The treatment of Pb poisoning involves chelation, which accelerates the process of reducing the Pb levels in the circulating blood. In children, chelation therapy is recommended only when the BLLs exceed 45 µg/dL (86). There is an abundance of evidence demonstrating that dietary calcium decreases gastrointestinal Pb absorption,

Outside mitochondria

Glycine + succinyl − COA Cyto C

ALA

Heme

Ferrochelatase (Heme synthetase) Pb∗

Fe2+ Protoporphyrin IX

ALA Dehydratase Pb∗

PROTO

COPRO

UROPOR

PBG

Figure 1. Scheme of heme synthesis showing sites where lead has an effect. PGB, phorbobilinogen; UROPOR, uroporphyrinogen; COPRO, coproporphrinogen; PROTO, protophorphyrinogen; Co A, coenzyme A; ALA, δ —aminolevulinic acid; Pb∗ site for Pb effect (from Ref. 68).

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thereby reducing Pb toxicity (87). Experiments carried out on rats suggest that bone Pb concentrations increased by about fourfold in rats fed with a low calcium diet, compared to rats on a normal calcium diet, although the amounts of Pb ingested were equal (88). Short-term intake of calcium does not alter BLLs, but reports suggest that under conditions of physiological stress, skeletal minerals can be mobilized for calcium and that Pb will also be released along with calcium during this mineral mobilization (72,89,90). Ongoing research is now addressing whether calcium intake will reduce this mobilization. Epidemiological studies have shown correlations between low levels of Pb contamination in the environment and subtle neurobehavioral effects in children. However, the biochemical mechanisms forming the basis of these subtle neurotoxic effects of low concentrations of Pb in the environment have not been clearly established (5). This is another area where research needs to be focused, to find out the biochemical interactions that may be primarily responsible for the neurotoxic effects of Pb.

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LEAD AND ITS HEALTH EFFECTS 30. Jones, R., Inouye, L., Bednar, A., and Boyd, R. (2004). Lead toxicity and subcellular compartmentalization in earthworms exposed to contaminated soil. The Society of Environmental Toxicology and Chemistry, 25th Annual Meeting, North America. Available at http://abstracts.co.allenpress.com/ pweb/setac2004/document/?ID=42021. 31. Doelman, P., Nieboer, G., Scrooten, J., and Visser, M. (1984). Antagonistic and synergistic toxic effects of Pb and Cd in a simple food chain: nematodes feeding on bacteria or fungi. Bull. Environ. Contam. Toxicol. 32: 717–723. 32. Beyer, W.N. and Anderson, A. (1985). Toxicity to woodlice of zinc and lead oxides added to soil litter. Ambio 14: 173–174. 33. Sanderson, G.C. and Bellrose, F.C. (1986). A Review of the Problem of Lead Poisoning in Waterfowl. Illinois Natural History Survey, Champaign, Illinois, Special Publication 4. Northern Prairie Wildlife Research Center Jamestown, ND. Available at http://www.npwrc.usgs.gov/resource/othrdata/ pbpoison/pbpoison.htm. 34. Pain, D.J. (1990). Lead shot ingestion by water birds in the Camargue, France: an investigation of levels and interspecific differences. Environ. Pollut. 66: 273–285. 35. United States Fish and Wildlife Service (USFWS) (1999). Establishing ‘‘lead free fishing areas’’ and the prohibition of the use of certain fishing sinkers and jigs made with lead on specific units of the National Wildlife Refuge System. Fed. Reg. 64(70). 36. Lead poisoning report (2000). 3rd International Update Report on Lead Poisoning in water birds. Available at http://www.wetlands.org/pubs&/Lead P Report.htm. 37. Burger, J. (1995). A risk assessment for lead in birds. Toxicol. Environ. Health 45(4): 369–396. 38. Boline, D.R. (1981). Some speciation and mechanistic aspects of trace metals in biological systems. In: Environmental Health Chemistry. J.D. McKinney (Ed.). Science, Ann Arbor. 39. Kelada, S.N., Shelton, E., Kaufmann, R.B., and Khoury, M.J. (2001). δ-Aminolevulenic acid dehydratase genotype and lead toxicity: a huge review. Am. J. Epidemiol. 154(1): 1–13. 40. Agency for Toxic Substances and Disease Registry (ATSDR) (2003). Case studies in environmental medicine. Lead toxicity. Available at http://www.atsdr.cdc.gov/HEC/CSEM/lead/ physiologic effects.html#Pregnancy%20Outcomes. 41. Lin–Fu, J.S. (1973). Vulnerability of children to lead exposure and toxicity: part one. N. Engl. J. Med. 289: 1229–1233. 42. Ziegler, E.E. et al. (1978). Absorption and retention of lead by infants. Pediatric Res. 12: 29–34. 43. Chamberlain, A.C. (1983). Effect of airborne lead on blood lead. Atmos. Environ. 17: 677–692. 44. Simons, T.J.B. (1986). Passive transport and binding of lead by human red blood cells. J. Physiol. 378: 267–286. 45. Barry, P.S. and Mossman, D.B. (1970). Lead concentrations in human tissues. Br. J. Ind. Med. 27: 339–351. 46. Schroeder, H.A. and Tipton, I.H. (1968). The human body burden of lead. Arch. Environ. Health 17: 965–978. 47. Finkelstein, Y., Markowitz, M.E., Rosen, J.F. (1998). Lowlevel lead-induced neurotoxicity in children: an update on central nervous system effects. Brain Res. Rev. 27: 168– 176. 48. Bressler, J.P. and Goldstein, G.W. (1991). Mechanisms of lead neurotoxicity. Biochem. Pharmacol. 41 (4): 479–484. 49. Damstra, T. (1977). Toxicological properties of lead. Environ. Health Perspect. 19: 297–307. 50. Blackman, S.A. (1937). The lesions of lead encephalitis in children. Bull. Johns Hopkins Hosp. 61: 1–61.

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51. Needleman, H.L., Schell, A., Bellinger, D., Leviton, A., and Allred, E.N. (1990). The long-term effects of exposure to low doses of lead in childhood. N. Engl. J. Med. 322: 83–88. 52. Bradbury, M.W.B. (1984). The structure and function of blood–brain barrier. Fed. Proc. 43: 186–190. 53. Clasen, R.A. et al. (1973). Electron microscopic and chemical studies of the vascular changes and edema of lead encephalopathy. Am. J. Pathol. 74: 215–240. 54. Goldstein, G.W., Asbury, A.K., and Diamond, I. (1974). Pathogenesis of lead encephalopathy. Uptake of lead and reaction of brain capillaries. Arch. Neurol. 31: 382–389. 55. Yule, X., Lansdown, R., Miller, I., and Urbanowicz, M. (1981). The relationship between blood lead concentrations, intelligence, and attainment in a school population: a pilot study. Dev. Med. Child Neurol. 23: 567– 576. 56. Schroeder, Sr., Hawk, B., Otto, D.A., et al. (1985). Separating the effects of lead and social factors on IQ. Environ. Res. 38: 144–154. 57. Fulton M., Raab, G., Thomson, G., et al. (1987). Influence of blood lead on the ability and attainment of children in Edinburgh. Lancet 1: 1221–1226. 58. Lansdown R., Yule, W., Urbanowicz, M.A., and Hunter, J. (1986). The relationship between blood–lead concentrations, intelligence, attainment and behavior in a school population: the second London study. Int. Arch. Occup. Environ. Health 57: 225–235. 59. Hawk, B.A., Schroeder, S.R., Robinson, G., et al. (1986). Relation of lead and social factors to IQ of low SES children: a partial replication. Am. J. Ment. Defic. 91: 178–183. 60. Winneke, G., Brockhaus, A., Ewers, U., et al. (1990). Results from the European multicenter study on lead neurotoxicity in children: implications for risk assessment. Neurotoxicol. Teratol. 12: 553–559. 61. Kehoe, R.A. (1961). The metabolism of lead in man in health and disease: present hygienic problems relating to the absorption of lead: the Harben 1960. J. Inst. Public Health. Hyg. 24: 177–203. 62. Seto, D. and Freeman, J.M. (1964). Lead neuropathy in childhood. Am. J. Dis. Child. 107: 337–342. 63. Xu, Bo., Chia, S.E., Tsakok, M., and Ong, C. (1993). Trace elements in blood and seminal plasma and their relationship to sperm quality. Reprod. Toxicol. 7: 613–618. 64. Alexander B.H. et al. (1996). Paternal occupational lead exposure and pregnancy outcome. Int. J. Occup. Environ. Health 2 (4): 280–285. 65. Lancranjan, I. et al. (1985). Reproductive ability of workmen occupationally exposed to lead. Arch. Environ. Health 30: 396–401. 66. Lerda, D. (1992). Study of sperm characteristics in persons occupationally exposed to lead. Am. J. Ind. Med. 22: 567–571. 67. Alexander, B.H. et al. (1996). Semen quality of men employed at a lead smelter. Occup. Environ. Med. 53: 411–416. 68. Chisolm, J.J., Jr. and O’Hara, D.M. (1982). Pb Absorption in Children: Management, Clinical and Environmental Aspects. Urban & Schwarzzenberg, Baltimore. 69. McMichael, A.J. et al. (1986). The Port Pirie Cohort study: maternal blood lead and pregnancy outcome. J. Epidemiol. Community Health 40: 18–25. 70. Barltrop, D. (1969). Transfer of lead to the human foetus. In: Mineral Metabolism in Paediatrics. D. Barltrop and W.L. Burland (Eds.). Blackwell, Oxford.

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71. Gershanik, J.J., Brooks, G.G., and Litle, J.A. (1974). Blood lead values in pregnant women and their offspring. Am. J. Obstet. Gynecol. 119: 508–511. 72. Gulson, B.L. et al. (1997). Dietary lead intakes for mother– child pairs and relevance to pharmacokinetic models. Environ. Health Perspect. 105: 1334–1342.

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73. Sanin, L.H. et al. (2001). Effect of maternal lead burden on infant and weight gain at one month of age among breastfed infants. Pediatrics 107(5): 1016–1023.

GALINA DIMITRIEVA-MOATS University of Idaho Moscow, Idaho

74. Nolan, C.V. and Shaikh, Z.A. (1992). Lead nephrotoxicity and associated disorders: biochemical mechanisms. Toxicology 73: 127–146. 75. Cramer, K., Goyer, R.A., Jagenburg, R. and Wilson, M.H. (1974). Renal ultra structure, renal function and parameters of lead toxicity in workers with different periods of lead exposure. Br. J. Ind. Med. 31: 113–119. 76. Dobryszycka, W. et al. (1984). Morphological and biochemical effects of chronic low level cadmium and lead feeding rats. Acta Pol. Pharm. 41: 111. 77. Lilis, R. et al. (1980). Kidney function and lead: relationships in several occupational groups with different levels of exposure. Am. J. Ind. Med. 1: 405–412. 78. Nuyts, G.D. et al. (1991). Does lead play a role in the development of chronic renal disease? Nephrol. Dial. Transplant. 6: 307–315. 79. Waldegger S. et al. (1995). Heavy metal inhibition of rBAT—induced amino acid transport. Kidney Int. 47(6): 1667–1681. 80. Victery W., Throler, H.A., Volpe, R., et al. (1988). Summary of discussion sessions: symposium on lead blood pressure relationships. Environ. Health Perspect. 78: 139–155. 81. Schwartz, J. (1995). Lead, blood pressure, and cardiovascular disease in men. Arch. Environ. Health 50: 31–37. 82. Korrick, S.A., Hunter, D.J., Rotnitzky, A., et al. (1999). Lead and hypertension in a sample of middle-aged women. Am. J. Public Health 89(3): 330–335. 83. Hu, H. et al. (1996). The relationship of bone and blood lead to hypertension. The normative aging study. JAMA 275: 1171–1176. 84. Warren, M.J., Cooper, J.B., Wood, S.P., and ShoolonginJordan, P.M. (1998). Lead poisoning, haem synthesis and 5-aminolaevulinic acid dehydratase. TIBS 23: 217–221. 85. Kappas, A., Sassa, S., Galbraith, R.A., and Nordmann, Y. (1995). In: The Metabolic Basis of Inherited Diseases, 7th Edn. Scriver, C.R., A.L. Beaudet, W.S. Sly, and D. Valle (Eds.). McGraw Hill, New York, pp. 2103–2159. 86. Centers for Disease Control (1991). Preventing Lead Poisoning in Young Children. A Statement by the Centers for Disease Control, United States Department of Health and Human Service, United States Public Health Service, Atlanta. 87. Bruening, K. et al. (1999). Dietary calcium intake of urban children at risk of lead poisoning. Env. Health Perspect. 107: 431–435. 88. Mahaffey, K.R. (1995). Environmental health issues—commentary on nutrition and lead: strategies for public health. Environ. Health Perspect. 103(S6): 191. 89. Gulson, B.L. et al. (1997). Pregnancy increases mobilization of lead from maternal skeleton. J. Lab. Clin. Med. 130: 51–62. 90. Gulson, B.L. et al. (1998). Mobilization of lead from the skeleton during the postnatal period is even larger than during pregnancy. J. Lab. Clin. Med. 131: 324–329.

GENERAL INTRODUCTION General The U.S. Environmental Protection Agency (U.S. EPA) persistently supports programs that monitor water resources using bioassessments and that develop biocriteria for different water bodies throughout the country in accordance with the Clear Water Act, the Watershed Protection Approach, and the National Water-Quality Assessment (NAWQA) Program. Currently, assessments of biological integrity and water quality are based on habitat measurements and also on biosurveys of the status of indicator aquatic communities. In order to evaluate an integrative ecological situation in water resources, the U.S. EPA has established protocols for bioassessments and for developing biocriteria applicable to selected biological assemblages, such as phytoplankton, zooplankton, periphyton, macrophytes, macroinvertebrates, and fish. As the U.S. EPA literature mentions, at the present time, no established protocols exist for other groups of organisms, including bacteria, because the data about those organisms are not sufficiently numerous. However, bioassessments based on the use of currently selected indicator groups of hydrobionts do not indicate the cause of water resource impairment. Also, usually habitat measurements monitor already known impairing factors; therefore, if a new pollutant has appeared, it may remain undetected. The author of this paper had long-term extensive experience working with water quality control and ecological integrity monitoring using microbial indices. This practice includes eight years of microbial bioassessments and the development of biocriteria implications for the detection of various organic pollutants, a number of heavy metals, and biological contamination in seawaters of Russia, which provided impressive results, demonstrating the advantages of such an approach for monitoring ecological integrity and water quality of estuaries and shallow and pelagic regions of marine coastal zones. The composition alteration of aquatic sediment or plankton microbial assemblages subjected to pollution resulted in an increase of pollutant-resistant (indicator) groups that detected expected and unexpected pollutants and their levels. The analysis of the proportion between all indicator groups assisted us in drawing conclusions about the natural or anthropogenic process or factors causing impairment of water resources. As monitoring of water quality using microbial indices and habitat metrics can detect many different pollutants at a number of monitoring stations, we gathered sample point

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data via a Global Positioning System (GPS) and displayed the distribution of each pollutant over the water body on maps employing a Geographic Information System (GIS). Several pollutants have been monitored using microbial assessments and habitat metrics, including measurements of toxic compounds at the reference stations and at the monitoring stations. Microbiological assessments for the evaluation of the biological contamination included controlling fecal and pathogenic bacteria, such as E. coli, Salmonella, Shigella, and Listeria, detecting phenolresistant bacteria as indicators of fecal phenols, and also evaluation of the proportion of proteolytics and lipolytics bacteria in microbial assemblages. In order to monitor the pollution of oil and oil by-products, we studied the percent of microorganisms resistant to those pollutants as well as the concentration of those compounds. The portion of lipolytic bacteria that might contribute to oil biodegradation was also detected and evaluated. We also applied microbiological assessments and habitat measurements in order to detect the presence and the origin of phenols that can appear in the water from point and nonpoint sources. The choice of monitored heavy metal pollution using microbial assessments, and also habitat metrics, was based on the environmental role of heavy metals and their impact. As a primer pool of elements, we controlled Cu, Pb, and Ni as indicators of industrial impact; Cd and Zn as indicators of anthropogenic impact; Co and Cs as detectors of radioactive contamination; and Fe as a marker of terrestrial influence. Historical Background Application of Microbial Assessments for Detection of Various Pollutants in the Environment

Response of Indicator Groups of Microorganisms to Pollution in the World Ocean. The concept of microbial indication of organic pollutants in the world ocean has been developed most actively during the last two decades. Progressively increasing anthropogenic load on the marine environment creates tense ecological situations, primarily in coastal areas. As had been established earlier, an increase of anthropogenic pressure on the marine environment influences structural and functional properties of hydrobiont communities (1). Pollutants cause various changes in marine organisms. Organisms that have adapted to new chemical compounds, or increased concentrations of pollutants in the environment, begin to dominate in the structure of biocenosis. The ability to quickly adapt to changing environmental conditions because of high rates of reproduction and growth and versatile enzymatic activity is a unique feature of microorganisms. For this reason, microorganisms are unique tools that scientists have started using to control marine pollution because they have the most direct connections to the surrounding environment, they react quickly by altering population size and composition, and they reflect any environmental changes. On this basis, microbial assemblages are considered indicators of physical, chemical, and biological processes in the world ocean (2–7). As is known, microorganisms are indicators of contamination of various organic substances, because

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they are destroyers and consumers of those compounds at the same time. The existence and sensitivity of the individual response of the plankton community to variations in the concentrations of metals in contaminated waters, with a complex of metals, are confirmed on the basis of microbiological data and the results of their comparison with the data of chemical analysis (8–11). A number of microorganisms, the composition of main physiological groups, and distinct genera in seawaters and sediments are characteristics of microbial assemblages that researchers used for the purposes of biomonitoring of pollutants in the marine environment (12–15). Biological contamination criteria were developed earlier, historically for fresh waters more than for seawaters. Microbial assessments of other kinds of pollution have longer records in the marine environment, particularly, in Russia.

Detection of Pathogenic Bacteria and Biological Contamination in Surface Waters. Indication of pathogenic microorganisms in surface waters is under the control of environmental services and laboratories. Observed indicator bacteria of biological contamination exist, as well as saprobe indices of waters in freshwater and seawater environments. Freshwater saprobe indices are established on the basis of the ratio between the number of bacteria grown on reach nutrient agar and the number of bacteria grown on pour agar at starving conditions. For barely contaminated sites, the ratio is 1.2–2.8, and for references, the ratio appears as 0.1–0.7 (16). Also, most of the microbial indicators of biological contamination have been studied in fresh waters. In the 1960s, seawaters in Russia were investigated and classified according to their saprobes (17). In the 1970s, indicator microorganisms for biological contamination were determined, and sanitary criteria were established according to international agreement (18,19). According to that classification, in secure waters, the number of Escherichia coli cells must not exceed 10 per mL. In 1 mL of dangerous waters that can cause infectious diseases, more than 24 cells were found. The control of biological contamination is also a very highly developed field at the present time. As seawaters accept an increasing amount of domestic and industrial wastewaters, the biological contamination of seawaters is a subject of the continuing investigation. Distribution of fecal and pathogenic bacteria has been studied in the waters of the Atlantic Ocean (20) and in the benthos coastal zone of the Antarctic Ocean (21). Other regions of the world ocean have been studied in estuarial (22), coastal (13), and pelagic (23) zones. Among the indicators of fecal contamination indicated are such microorganisms as E. coli, Nitrobacteria spp., Clostridium perfringens, Pseudomonas aeruginosa, Vibrio spp., Salmonella spp., Candida albicans, Klevsiella spp., Bacterioides spp., enterococci, bifid-bacteria, and fecal streptococci (22). Intestinal viruses are also the subject of study in the water environments. Use of Microorganisms as Indicators of Oil Pollution in Seawaters. Microorganisms were beginning to be used many years ago as detectors of oil pollution and of water quality in the marine environment. One of the

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first marine microbiologists studying this subject was ZoBell and his coauthors (24). These scientists have found more than 100 species of marine microbes representing 30 genera, which have been able to use hydrocarbons. Those microorganisms have been considered indicators of oil pollution in seawaters. By the present time, researchers have isolated more than 1000 strains of microorganism-oxidizing hydrocarbons (25–28). The most active hydrocarbon-oxidizing marine bacteria were determined to be Mycobacterium and Arthobacter (29). In Russia, the first publications devoted to indication of oil contamination in seawaters were published in the 1950s (30,31). The evaluation criteria for oil pollution were based on the ratio of oil-oxidizing heterotrophic bacteria and saprotrophic bacteria or on the ratio of oiloxidizing bacteria and the total bacterial quantity (29,32). Bacterial criteria for determining acceptable standards for clean water were also established. More recently, data appeared about microbial degradation of not only aliphatic hydrocarbons, but also of polycyclic hydrocarbons (33–35). Their results have demonstrated that indicator groups of microorganisms are developed weakly in noncontaminated pelagic seawaters. In oilcontaminated areas of the world ocean, those groups were very numerous. For this reason, researchers use the activity and a number of hydrocarbon-oxidizing microorganisms as an index of oil pollution in seawaters. Now this is the most heavily investigated field in the study of marine microbiology in Russia and in the world at large.

Microbial Detection of Phenols in Seawaters. Contamination of surface waters by phenols can have different origins. Fecal sterols, polyaromatic hydrocarbons, biphenyls, and Cl-phenols enter water environments from domestic wastewaters, from industrial oil pollution, from oil spills, and from cellulose factories. Contrary to microbial indication of oil pollution in seawaters, indication of phenols does not have long-term records. Over more than twenty years, some articles devoted to microbial detection of phenols in seawaters were published (7,36,37). The microbial detection of fecal sterols (38–40), Clphenols, and biphenyls has been studied in more detail (1,15). Microorganisms and degrading aromatic phenols are considered as indicators of phenol pollution in deep-water regions of the ocean (7,36,41). Remarkably, the composition of microbial assemblages from phenolcontaminated seawaters and marine sediments has been found to be close to the composition of the microbial community from active silts of wastewater treatment facilities, which were adapted to phenol by-products (42). Representatives from genera Bacillus (25%), Pseudomonas (12.5%), Mycobacterium (24%), Micrococcus (25%), and Actinomyces (12.5%) were found there. However, no indices were established to confirm the phenol contamination in the marine environment. Bacteria-Degrading Lipids, Proteins, and Starch Are Additional Indicators of Organic Contamination in Coastal Waters. Seawater and marine neuston organisms contain considerable amounts of various lipids. The concentration

of lipids in seawater varies from 0.01 to 0.12 mg·mL−1 , and concentration of lipids in marine plankton appears as 2–25%. Also, three gycerides, fatty acids, and phospholipids are oil by-products during the oil transformation process in the marine environment and bacteria synthesize them as well. As lipids are much lighter than water, they are concentrated on the margin of the surface of seawater and interfere with the gas and temperature exchange process between the ocean and the atmosphere, causing different negative consequences. Many marine bacteria can use lipids as a source of carbon. They possess lipolytic activity and provide self-clearance of lipids from seawaters. Bacterial neuston is particularly important for the biodegradation of lipids in the sea (43). For this reason, some authors suggest considering the appearance of lipolytic activity in the dominant part of neuston microbial assemblages, as confirmation of the presence of oil contamination in seawater. Determination of a number of lipolytic microflora and measurement of lipolytic activity in marine bacteria serves as a test, characterizing the capability of the marine coastal environment for self-clearance (43,44). Nitcowski et al. (12) presented data in evaluating a portion of the physiological groups of lipolytic microorganisms in aquatic microbial association, as well as a portion of proteolytics, as an indicator of biological contamination. The authors have found that a number of bacteria from those groups were four times as numerous at contaminated sites. Among those physiological groups of microbes, 80% of the population has been identified as pseudomonades and vibrions. Some marine bacteria, yeasts, and fungi are capable of degrading starch. Such microorganisms were detected among microbial assemblages living on the surface of marine algae and plants (45–47), their remains (44,46), and in the water (45). In our opinion, such microorganisms may also indicate contamination of seawaters by carbohydrates. Application of Microbial Biosurveys for Detection of Heavy Metal Contamination in the Environment Practical use of the microbial approach for detection of the presence of metals started in the 1950s in geological survey practice for the metal ore search in Russia. The method was based on the ability of certain bacteria to stimulate or to inhibit their growth in response to the presence of metals of interest in the ground and in the surface waters (48,49). In order to prove that the method of microbial detection can be implicated for metal deposit searches, scientists used the station grid approach, where habitat metrics included measurements of the concentrations of metals. Such field investigations covered extensive areas in different states and republics of the former Soviet Union in Eastern Siberia, Kazakhstan, Ural, and the Caucasus regions. Researchers have found a direct connection between the distribution of metals (Mo, Zn, Cu) and a number of cultured, metal-resistant, or metal-sensitive bacteria. All other similar applications in geological microbiology were reviewed later (50). In the 1970s, the geochemical ecology of microorganisms was established as a science in Russia. The subject of

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

geochemical ecology of microorganisms is the study of interactions between natural and industrial factors, including metals, in the environment (51,52). At the present time, environmental microbiology studies mechanisms of the interaction between microorganisms and heavy metals. Microorganisms absorb metals for their physiological needs, as do many other organisms, because metals are an important part of biological molecules, including enzymes, hormones, vitamins, pigments, and lipids. Generated data demonstrate that microorganisms also have a unique system of cell organization and function, responsible for selective binding and absorption of metals by bacteria. The major element of this system is the cell wall. It is remarkable that the adsorptive capability of bacterial cell walls is so high and that it is comparable with the most efficient resins used for ionexchange chromatography (53). As now established, the selective adsorption of distinct metals by cell walls varies significantly in different bacteria (52–54). In firmicutes, an affinity of cell walls in binding different metals is presented as follows: La3+ > Cd2+ > Sr2+ > Ca2+ > Mg2+ > K+ > Na+ > Li+ (53). As a result of such high capability of the selective binding of metals, bacteria accumulate metals that greatly exceed the natural concentrations of metals in the environment. The absorption process involves active and passive transport of metals through the plasma membrane. Specificity of active transport mechanisms is based on ligands selective to individual metals. Those minor membrane protein structures are a second element of the system responsible for selective binding and absorption of metals by bacteria. For example, it has been demonstrated that E. coli has three specific systems for transport of iron (55). Bacteria have a high resistance to heavy metals because of different mechanisms of their detoxification. For this reason, microorganisms are the only live organisms on the Earth that are able to live in environments containing very high concentrations of heavy metals. The detoxification of heavy metals is the system that provides bacterial survival in heavy metal environments. In general, those mechanisms include: limitation or complete blocking of metal internalization into bacterial cells, active removal of absorbed metals from cells, and detoxification of metal ions by binding and transforming them into nontoxic forms or by the resulting intracellular accumulation (56,57). Thus, bacteria possess various mechanisms of self-protection against toxic effects of heavy metals in the environment. On the basis of presented data, we may conclude that the variety of systems of selective binding and transport of heavy metals, and also the system of detoxification of heavy metals, are real cell functions that provide survival and the specific response of the microbial community to the presence of toxic metals in the aquatic and terrestrial environments. Of course, passive transport and nonspecific transport of metals also take place in microbial cells. Other mechanisms of interaction of bacteria with metals exist as well, but it is not an aim of this entry to discuss all aspects of the interaction of bacteria with metals, including details of detoxification of metals by microbial cells. Those aspects are presented in other papers (56–61). Also,

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many environmental factors influence the efficiency of the interaction of metal ions with microbial cells, including the pH of various environments, the state of metal ions, and the presence of other ions (56). The information presented above aims to demonstrate a general knowledge that may help in the understanding of the true foundation for the prospective use of microbial assessments for monitoring heavy metals in water environments. However, this powerful tool for environmental monitoring is not yet widely used. Also, since recent times, the technique of microbial survey, employed to indicate different pollutants, their concentrations, and also the ecological state of marine or freshwater environments, was not sufficiently used in Russia, or in the remainder of the world for that matter. Monitoring Marine Environmental Quality in Russia The anthropogenic load and its influence on the condition of the world ocean, particularly in the marine coastal zones, continues to grow as a result of population growth and increasing human activity. Such pressure influences qualitative development of sea life and the structural and functional characteristics of hydrobiont assemblages in the ecological, morphological, physiological, biochemical, and genetic levels (1). One of the most important consequences of the pollution of the marine environment is an appearance of indicator forms that can possess harmful characteristics, which is one of the reasons why the methods for biological control of marine environmental quality were developed in the 1960s. Two major different strategic approaches have been applied for biomonitoring of pollution in the marine environment in Russia in the past. These approaches are bioassay and bioindication. Microbial detection of marine pollutants combines the advantages of both methods and gives new possibilities for efficient tracking of pollutants issued from point and nonpoint sources in surface waters. Bioassay Approach. The bioassay approach is based on the ability of marine organisms to react through their longevity, by the reduction of some life functions, and by alteration of cell structure at the appearance and concentration of toxic compounds in the seawater. These variations are immediately observable and provide information about the degree of toxicity of the environmental samples containing the complex of pollutants for certain kinds of organisms. However, this method does not provide information about the concentration of pollutants or an indication of which pollutant causes this negative effect. The most suitable subjects used for such control are microalgae, larvae of marine invertebrates, young generations of fishes (62,63), sea urchins and molluscs, and also sexual cells of marine organisms and marine polychaete (64). Usually, those subjects are single cell or simply organized forms, which are very sensitive to unfavorable conditions and have short lifespans. Bioindication Approach. Another technique widely used for the marine environmental quality control is bioindication, which pertains to the study of mature, long-term life

444

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

forms and requires that organism monitors must be immobile or attached to the marine substrate, and that they must be resistant to pollution and also able to accumulate toxic compounds at a concentration exceeding environmentally acceptable levels to several significant digits. The organisms most often used for bioindication in the marine environment are macroalgae and molluscs (65). These organisms are used particularly to monitor heavy metals in seawaters. In such cases, chemical analysis of the organism’s tissues displays every distinct pollutant and establishes the dynamic of its behavior in the marine environment over time. The disadvantage of this approach is that no information about how toxic a certain compound may be and what the concentration of that chemical was during a certain period may be determined. Use of a Combination of the Bioassay and Bioindication Methods in Russia. The use of both the bioassay and bioindication methods in Russia is mostly applicable to scientific research at the present time. Currently, no state regulation of these methods exists in environmental policy. However, because such approaches are numerous and multidisciplinary, Russian Scientific Institutes always are afforded opportunities to submit results of expertise and to make strong recommendations to any federal government or local state and city organizations and agencies to influence their economical or political solutions. Such scientific investigations are always a subject of consideration for the Environmental Protection Committees and Ministry, and also for the Health Protection Ministry and the local Sanitary Committees of Russia. It is fortunate to note that most of the time their final decisions are taken with consideration of the recommendations given by Scientific Organizations monitoring the marine environmental quality and condition of marine habitats. For example, several scientific marine institutions conducted long-term and multidisciplinary investigations of the ecological state of the marine environment in the important international economical zone near Vladivostok, Russia during 1996–1998. Named The Tumen River Economic Development Area Project (TREDA), it was planned by the United Nations Organization to help economical and political development of that Pacific Region, involving China, North Korea, Japan, and Russia. The first initiative was considered the only economic side of that project. No detailed information existed about the current complex ecological situation of the area and how the project application could change the surrounding marine environment. The existence of the unique Marine National Reservation in Russia was not considered at all. Subsequently, scientific investigations showed that nobody controlled the flow of wastewater into the Tumen River from China and North Korea; consequently, the pollution at this site has increased tremendously during recent years. The increased flow of domestic, agricultural, and industrial wastewaters into the Sea of Japan caused the appearance of many unhealthy forms among the marine habitats in the Marine State Reservation area. The expertise conducted made responsible persons and organizations plan additional efforts and funding to protect not only the Russian National Marine Reservation

but also the marine environment of the Sea of Japan. I am proud to announce that microbial detection results of those dramatic changes were among the first data obtained through these efforts. MICROBIAL BIOSURVEYS IN FAR EASTERN SEAS OF RUSSIA Areas of Field Investigations We began our investigation in this field 12 years ago. The areas that have been investigated in the Russian Pacific region have all involved international, economically, and politically important areas (Fig. 1), such as the Southeast Pacific Ocean coast of the Kamchatka peninsula (1995, 1997, 1999), the southwest (1995, 1997) and the northeast (1996, 1998) of Sakhalin island, and the North (1992, 1996–2000) and South parts of Primorie (1995–2001) (8–11,37,47,66–68). As a matter of background, the Far Eastern seas are influenced by global natural factors such as the Pacific ore ‘‘belt,’’ volcanic activity, grand streams, upwelling, and by the action of bringing chemical elements to the surface water in active geochemical zones. As a result, the Far Eastern seas are distinguished as containing the highest level of toxic material, primarily heavy metals, which can provoke ecological stress and cause pollution. Every water body chosen for our investigation had specific characteristics and was distinguished in the degree of anthropogenic impact, geochemical, geographic, and ecological conditions. In the past, Avachinskaya Guba Bay, Krasheninnikov Bight (Kamchatka peninsula) was known as the biggest Russian Navy base, and because of this status, the area became contaminated with radionuclides. Seawaters surrounding Sakhalin Island are

Figure 1. Areas of the studies on microbial indication of pollution of the near-shore waters by heavy metals: I—Kamchatka coast, area of Avachinskaya Guba; II—northeastern coast of Sakhalin Island, Nyiskii, Nabil’, and Chaivo Bays; III—southwestern coast of Sakhalin Island, off Kholmsk; IV—Northern Primorie, Rudnaya Bight, and Lidovka Bights; V—Peter the Great Bay, the area of the mouth of the Tumen River Amur and Ussuri Bays, and Nakhodka Bight.

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

the most biologically productive in the Russian Far East and are used as one of the major international fishery regions. However, this region is affected by a strong anthropogenic impact. The waters near the Kholmsk area (South-West Sakhalin) is under the influence of the Tsushima Current, which carries oil, phenol, and heavy metal pollution from the coast of Japan. The shallow waters of bays of Northeast Sakhalin (Nyiski, Chaivo, and Nabil Bays) undergo oil extraction. The Russian coast of the Sea of Japan (the Primorie region) is also an important local fishery and an international transportation and trade zone. Rudnaya Bay (Northern Primorie) lies within the region of production and processing of polymetal ores rich in lead, zinc, and also containing a great admixture of copper, cadmium, or rare-earth metals. Traditionally, that aquatic area has been investigated because of its particular characteristic of extensive heavy metal contamination. Kit Bay (Northern Primorie), one of the cleanest parts of the Primorie coast, was used as a reference site for the investigation. Peter the Great Bay (Southern Primorie) presented itself as a rare type of habitat for aquatic life possessing unique geographic conditions, where the cold water of the Primorie stream mixes with the warm waters of the South Eastern Korean stream (a branch of the Tsushima Current) (69). The bay includes a highly productive shelf with a unique cenosis of aquatics. This area is composed of the only State Marine Reservation of Russia, the mouth of the Tumen River, Amur Bay, Ussuri Bay, Nakhodka Bight, and Golden Horn Bight (1995–2001). At the northwest end of Peter the Great Bay lie Golden Horn Bight, Amur Bay, Ussury Bay, and Nakhodka Bight, which are affected by the severe influence of domestic and industrial wastewaters from Vladivostok, Nakhodka, and other settlements. The ecological situation in the southwest part of Peter the Great Bay, during the longer warm period of the year, is determined by the influence of Tumen River running through industrial zones of China and North Korea. The State Marine Reservation is severely impacted by the pollution carried by that big river. Parameters Analyzed In selected aquatoria, a seasonal and monthly microbiological and chemical monitoring of the water quality was conducted. The following parameters were analyzed: (1) the number of colony-forming heterotrophic microorganisms and the proportion of metal-resistant groups of bacteria in the assemblages of colony-forming heterotrophic microorganisms in the near-surface and near-bottom water layers; (2) long-term variations in the number of metal-resistant colony-forming hetertrophic microorganisms; (3) seasonal dynamics in the number of metal-resistant colony-forming hetertrophic microorganisms; and (4) morphological, physiological, biochemichal, and molecular genetic peculiarities of metal-resistant heterotrophic microorganisms. All listed parameters have been investigated at reference sites and at impact sites. Microbiological monitoring and chemical analyses were performed simultaneously on water samples from areas that had been subjected to a pronounced anthropogenic

445

impact. Special selective media were developed in laboratory experiments and corrected during field observations for the selection of heterotrophic microorganisms that were highly resistant to contaminants. The composition of the pollutant-resistant groups of marine microbial communities was determined under conditions differing in the type of the anthropogenic impact and geochemical features. Monitoring of Heavy Metal Contamination in Seawaters Using Microbial Biosurveys The composition of microbial assemblages and also of physiological, biochemical, morphological, and molecular genetic characteristics of bacterial representatives were distinct in the contaminated and reference sites. However, because coastal seawaters usually contained a complex of pollutants, it was difficult to conclude which compound or factor caused that alteration. Only a number of bacteria in the planktonic microbial communities were resistant to each pollutant and seemed to be a clear indicator to characterize the presence of the distinct polluting compound and the degree of contamination. On the basis of the comparisons between the results from the synchronously conducted microbiological and chemical monitoring of the pollution of the near-shore seawaters, a positive correlation was established between the microbial indices of the abundance of resistant forms and the concentrations of each of the metal-treated and organic compounds. The microbial monitoring of heavy metal pollution was the least developed method. Therefore, as an example, I chose to demonstrate the approach of developing a microbial assessment for heavy metal monitoring in seawaters. Design of Selective Media The first step needed for the implication of microbial biosurveys was to design selective media that would allow calculation of a number of pollutant-resistant microorganisms in the water. A number of representative bacteria that commonly occur in coastal seawaters have been chosen in order to define the sensitivity of microorganisms to heavy metals. Bacteria of genera Escherichia, Pseudomonas, and Bacillus from laboratory collections that did not demonstrate a special resistance to metals were grown in nutrient media, containing metal salt at different concentrations. Every species has an individual sensitivity to the toxic metals. The concentration of a compound that completely inhibited any bacterial growth was considered as a selective factor and then used in selective media in order to detect the appearance and the proportion of metal-resistant microorganisms. As Fig. 2 demonstrates, the reverse correlation took place between the content of metal in the media and the growth of bacteria, if microorganisms did not have the resistance to the introduced toxic compound. However, when metal contamination is present in water, an abundance of microorganisms resistant to contaminating factors appear among the aquatic microbial communities. The illustration below demonstrates a negative correlation between the concentration of heavy metals and number

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

1.2

0.2

0

0 1

2

3 4 Variants

5

6

Figure 2. Dependence of bacterial growth on metal concentration in the growth medium.

of surviving microorganisms in the same samples of seawaters. Chemical and Microbiological Monitoring of Heavy Metals in Seawaters of Peter the Great Bay The synchronous sampling of heavy metal contents in the northern part of Peter the Great Bay allowed us to compare the results obtained. As graphs demonstrate (Fig. 3a–c), the alteration of a number of the bacteria resistant to heavy metals is an agreement with the concentration of dissolved forms of corresponding metal in the water. We can observe individual response of microbial community to the content of metals in different concentrations in the water under complex pollution conditions in Peter the Great Bay. It points to the existence and sensitivity of the individual response of microbial populations to the content of metals in different concentrations in the water under complex pollution. Moreover, in the case of each heavy metal, the dynamic of that alteration occurs differently within certain intervals of metal concentration. The boundaries between gradual and drastic variations of microbial indices were very clear, which allowed us to formulate microbial criteria that might adequately detect the concentration range of heavy metals in the water. Average value of the percentage of the metal-resistant forms of bacteria in planktonic and benthal microbial assemblages allows comparison of the water quality from different parts of the large body of water. Moreover, microbial indices indicate from which part of the aquatorium the pollutant enters, from the surface or from the bottom. The next illustration demonstrates such a comparison made on the basis of microbial assessments conducted in several bights and secondary bays of Peter the Great Bay during the summer months of June–August of 1999 (Fig. 4a–d). Morphological Features of Marine Bacteria Inhabiting Contaminated Waters of Peter the Great Bay Golden Horn Bight is one of the most impaired water bodies among other bights of Peter the Great Bay. Fishery fleets, trade fleets, the military ship yard, and the city ferry transportation system are among industrial polluters of that aquatorium. Analysis of the morphological characteristics of bacteria in the planktonic assemblages can serve as an indirect characteristic of water pollution. It is a well-known fact that in heavily contaminated marine areas, rod-shaped (over 87%) and gram-negative (over

8 6 4 2 0 1

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Cd

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

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Cu concentration, Mkg/L

60

(a)

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1

Zn concentration, Mkg/L

Cd concentration, mg /mL

80

Cfux1000/mL

446

6

Figure 3. Changes in the values of microbial indices (line MI) and concentration of dissolved forms of metals in the water samples taken from Ussuri Bay: (a) copper, (b) cadmium, and (c) zinc. Along the horizontal axis, the station numbers were sorted with respect to increasing concentrations of heavy metal in the water.

60%) microflora prevail (70). We conducted microscopic examinations of 117 strains isolated from the nearsurface water layer in the central part of Golden Horn Bight, Vladivostok, Russia. Among all microorganisms cultivated, rod-shaped bacteria made up 92%, and 72% of the bacteria were gram-negative. The isolated microorganisms were resistant to several heavy metals at a time, but the combination of metals and the range of bacterial resistance were different, which once again confirms the individual character of microorganism response to the pollutant concentrations in the environment. The use of a transmission electron microscope demonstrated typical symptoms of absorbing specific substances from the environment in both bacilli and cocci and their accumulation both inside the cells and in the cell wall (11). Although these substances were not identified, but based on the electron density of the substances and the detection of multiple metal resistances

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY (a)

Cfu/mL, %

15

Number of Cd-resistant bacteria in water bodies of Peter the Great Bay

10

Near-suface water

5

Near-bottom water

0

(b) 60

1 3 2 Amur Ussuri Nakhodka Bays Number of Pb-resistant bacteria in water bodies of Peter the Great Bay

Cfu/mL, %

50 Near-suface water

40 30

Near-bottom water

20

447

ampicillin in the concentration of 250 mg/mL (71). Electrophoresis analysis of plasmid DNA from eight strains detected the presence of a small plasmid with a molecular mass of 4 MD in the form of a monomer, dimer, or trimer that were identical to marker plasmid p2728, containing transposon Tn 501 and designed from pUC19 and encoding resistance to Hg and ampicillin (72). Thus, we have demonstrated that marine bacteria, as well as terrestrial bacteria, possess cell mechanisms providing resistance to heavy metals. We assume that numerous bacteria with such morphological and molecular genetic features could serve as indicators of environmental disturbance and contamination in the investigated areas. The presence of such bacteria also suggests the active participation of microbial communities in the process of transformation of substances finding their way into the environment. Depending on the phenomena in question, marine microbial cenoses can act both as indicators of physicochemical and biological processes and as a powerful biotic factor promoting the elimination of pollutants from the marine environment.

10 0

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Number of Cu-resistant bacteria in the water bodies of Peter the Great Bay Near-suface water

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Microbial Assessments for Evaluation of Heavy Metal Pollution Level in the Water of Far East Seas

1 2 3 Amur Ussuri Nakhodka Bays Number of Cs-resistant bacteria in water bodies of Peter the Great Bay Near-suface water Near-bottom water 1 2 3 Amur Ussuri Nakhodka Bays

Figure 4. Average value of the number of metal-resistant bacteria in near-surface and near-bottom water samples taken from different water bodies of Peter the Great Bay in June–August of 1999.

in the test bacteria, we assumed that we had observed accumulation of heavy metals by the marine bacteria. Study of the molecular genetics of Cd-resistant bacteria was also carried out. It was established that all Cd-resistant strains also displayed resistance to antibiotic

Comparison of Environmental Conditions in Different Regions of Far Eastern Seas Using Microbial Biosurveys. Investigations carried out in a number of regions of Far Eastern seas, having distinguished impacts and ecological situations, resulted in data that confirmed the informative efficiency of the use of microbial assessments for the evaluation of water quality and ecological integrity in the marine environments over geographic and environmental variations taking place in different regions (Table 1). For example, the data from Table 1 on the microbial detection of heavy metal pollution of Avachinskaya Guba show the presence of a significant portion of cobalt (Co)and cesium (Cs)-tolerant microorganisms in the microbial associations in the areas where an increased content of radionuclides, such as Co-60 and Cs-137, had formerly been found (73). Krasheninnikov Bay (Fleet harbor), which has been exposed to a pronounced technogenic and anthropogenic impact, is the most contaminated by a complex of heavy metals in this aquatic area. Near the southwestern seaboard of Sakhalin Island (off Kholmsk), the microbial indication confirms the known intense influence of the Tsushima Current on the content of heavy metals in the water (65). In northern Primorie, in Rudnaya Bight, the microbial characteristics reflect the features in the composition of the lead ores mined and the intensity of the technogenic load. The distribution of the metal-resistant groups of microorganisms is the least uniform in Peter the Great Bay, which is caused by the active hydrodynamics and the presence of a large number of sources of heavy metal pollution of both natural and anthropogenic character. Nakhodka Bight, where major commercial, oil, and fishery ports, together with several dockyards are concentrated, is the region most contaminated by complex heavy metals. Application of Microbial Assessments for Long-Term Monitoring and Evaluation of Water Quality in the Marine Environment. Long-term observation can give very important

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MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

Table 1. Relative Abundance of Metal-Resistant Forms (%) with Respect to the Total Amount of the Colony-Forming Heterotrophic Microorganisms in the Near-Shore Waters for Selected Aquatic Areas of the Far Eastern Seas Kamchatka Peninsula, Avachinskaya Guba July 1999 Bacteria, Resistant to Metal Co Cs Cd Zn Ni Cu Pb Fe

Sakhalin Island, Southwest, May 1997

Fleet Harbor

Malaya Sarannaya Bay, Reference

13 25 0 57.3 4.6 3 24.5 0

0 2.3 0 0.6 0 0 0.08 0

Northern Primorie, Polymetal Ore Mining, July 1999

Peter The Great Bay, July 1999

Kholmsk

Ore River Mouth

8 km to the South, Reference

Nakhodka Bight, Next to the Shipyard

Big Peles Island, Marine Reservation

3 16 7 1.6 15 15.9 10 16.1

6.4 19 0.5 14.3 25.3 7.4 0.12 0

0 9.8 0 0.6 5.8 0 0 0

2.5 10.6 4.4 62.6 3.9 40.1 87.2 41.2

0 4.7 0 2.3 0.02 0 0 0

environmental information about the intensity of anthropogenic and industrial load on water bodies. Table 2 demonstrates the dynamic of the presence of metalresistant forms of bacteria in seawater of the port, where Pb-Zn concentrate is transported by sea along the coast, which is located next to the lead smelter in Rudnaya Bight (see Fig. 5). Once again, when microbial indices are compared with the data of chemical analysis, they were in agreement. Moreover, both data of chemical and microbiological monitoring reflected the intensity of the ore processing and the production of the lead concentrate over time. Years 1997 and 2000 are known as a period of intensive ore processing and the operation of the lead smelter at full production. On the contrary, the situation during 1998–1999 resulted in a drop in the volume of extracted and processed ore because of the general economic recession and long-term forced inactivity of the plant. The dynamics of the microbial assessments remarkably accurately reflect the environmental situation in Rudnaya Bight during that period.

Use of GIS Technology to Indicate Concentrations of Heavy Metals Found in Marine Sediments and to Show the Distribution of Metal-Resistant Bacteria in the Water. In the southwestern part of the bay, the environmental situation is mainly determined by the effect of the Tumen River flowing through the industrialized regions of China and North Korea. From the data of the microbiological analysis of this area, we found that stations located in the zone of riverine runoff waters were characterized in a state where the entire association of microorganisms cultivated showed an increased resistance to the presence of Ni, Zn, and Fe in the environment. In the communities mentioned, there exists a considerable portion of bacteria with an increased resistance to the presence of Cd, Pb, Cu, Co, and Cs in the environment. The data from the chemical analysis and the determination of the content of heavy metals in the tissues of hydrobionts confirm the contamination of the aquatic area by the pollutants listed in the scientific report (74). With a sufficient density in the network of monitoring stations, the data from microbial indication may be applied to preliminary biogeochemical

Table 2. A Number of the Highly Phenol-Resistant and Oil-Resistant Colony-Forming Heterotrophic Microorganisms (103 per mL) in the Near-Shore Waters for Selected Aquatic Areas of the Far Eastern Seas

Region

Microbial Groups Heterotrophic bacteria Destroyers of: Oil Fuel oil Engine fuel Phenol

Kamchatka Peninsula, Avachinskaya Guba Bay, April 1996

Sakhalin Island, Southwest, Kholmsk, May 1997

Fleet Harbor

Ocean Waters, 5 km from Coast, Reference

Port

800 ± 130

500 ± 110

600 ± 3

40 ± 8 90 ± 7 7±1 0

2 ± 0.3 3 ± 0.3 10 ± 2 0

100 ± 20 4 ± 0.7 2 ± 0.1 0.05 ± 0

Destroyers Pulp and Paper Plant 400 ± 3

20 ± 0.1 30 ± 0.2 0 20 ± 0

Northwest Sakhalin, Nyi Bay, August 1996

Peter the Great Bay, July 1999

Exit into Sea

Oil Drill

Amur Bay, Next to Domestic Wastewater

3000 ± 300

1000 ± 80

24000 ± 307

1 ± 0.1 0.1 ± 0.01 10 ± 0.8 0.003 ± 0

40 ± 4 40 ± 1 0.7 ± 0.08 0

130 ± 15 100 ± 16 20 ± 4 3 ± 0.25

Big Peles Island, Reservation 60 ± 5

3±0 0.8 ± 0.001 0 0

MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

Percent of Pb-resistant forms of bacteria in the seawater 100

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1 0.5 0

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4 2000

Figure 5. Long-term dynamics of the percent of metal-resistant forms of bacteria in the near-surface water layer of the Rudnaya Bight. Reference station was 2 miles away from the lead smelter.

mapping of the near-shore aquatic areas, which was demonstrated by the example in the area off the mouth of the Tumen River for two of the eight heavy metals analyzed (Fig. 6). Use of Microbial Biosurveys for Assessments of Organic Pollution in Seawater. Microbial assessments proved to be even more efficient for monitoring organic pollution. This statement is based on the ability of microorganisms to use organic compounds as a source of carbon and energy. As it was reviewed above, the presence of such chemicals results in an increase of bacteria using hydrocarbons for their living needs. As Table 3 demonstrates, microbial criteria at reference sites are significantly less than at impact areas. Also, microbial assessments give information about sources of the contamination. For example, phenols can be a part of fecal contamination or they can be the result of the waste from cellulose processing. Seawater samples contained phenol destroyers taken either from places where a number of ships are present (Kholmsk, Port; Nyi Bay, exit to the sea), near the domestic wastewater dumping site (in Amur Bay), or next to plants manufacturing products from cellulose (Kholmsk, paper plant). Aside from the case of the paper plant, the number of phenol destroyers was ten times as much in comparison to fecal contaminated sites and correlated with concentrations of phenol in contaminated waters. A number of microorganisms destroying oil and oil byproducts also had a connection with the content of those

chemicals in the water. The presence of point or nonpoint contaminating sources close to the beach explains the reason for distribution of those specific microorganisms in the coastal waters. Moreover, the proportion between bacteria resistant to different oil by-products reflected the presence of those particular chemicals in seawaters, which may even explain the origin of the contaminant detected far away from land. For example, it is understandable why the water samples taken from port aquatoria have a significant number of oil and fuel oil microbial destroyers (Kamchatka, Fleet harbor). However, isolation of engine fuel microbial users from the surface of the open ocean water far away from Fleet harbor may cause us to think that bacteria trace the passage of ships that use that kind of fuel. Example of the Implications of Microbial Criteria for Water Quality Control of Seawater in the Seas of Far East Russia. After years of monitoring the water quality in a large number of water bodies using microbial assessments and chemical habitat metrics, we worked out criteria that can be used for monitoring ecological situations and the quality of seawaters (Table 4). Those criteria can be used during the first evaluation of water samples in order to receive general information about the ecological status of the water body. Then, criteria should be adjusted with respect to all other metrics measured in the water. Use of criteria, covering a wide number of polluting factors, gives information about the incredible value of

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MICROBIAL DETECTION OF VARIOUS POLLUTANTS AS AN EARLY WARNING SYSTEM FOR MONITORING OF WATER QUALITY

2 4

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Figure 6. Distribution of the metal-resistant forms of bacteria over the aquatic area adjacent to the mouth of the Tumen River: (left) Cu- and (right) Co-resistant forms. Concentrations of metals in the bottom sediments (in µg/kg of dry mass) are given within the squares; microbial indices (%) are given in the circles.

presenting the data on ecological integrity of the marine environment at the moment. On the basis of data received by a number of scientists over a long-term period, we can conclude that application of microbial criteria and microbial assessments is shown to serve as an operative method of monitoring and short-term forecasting of changes in the environmental conditions of the coastal waters of the sea. This method allows us to

this global approach, because we can present data on the ecological integrity of a larger system and complete an environmental situation report about the marine or freshwater water body. Table 4 demonstrates the use and advantage of the microbial assessments for the evaluation of the environmental water quality in the example of data, presented above. The use of symbols better assists in

Table 3. Criteria of Water Area Contamination on the Basis of Microbial Characteristics in Absolute Figures or in Percentage to the Maximum Number of Colony-Forming Microorganisms per 1 mL of Seawater Level of Contamination Pollutant Heterotrophic bacteria Oil by-products Phenol Pathogenic bacteria Intestinal bacteria Proteins Polysaccharides Lipids Metals Cadmium Cobalt Cesium Lead Copper Zinc Nickel Iron Symbol a

Background (Below the MAC)a

Insignificant (Around 1 MAC)a

Perceptible (1–3 MAC)

Considerable (Over 3 MAC)

Strong (Over 10 MAC)

107

10–103 0 0

>103 < 104 1–9 —

104 –105 10–103 various

0 40% >46%

>24 — — —